#
ES BEST-SELLING AUTHOR
MICHAEL
LEWIS
A WALL STREET REVOLT
FLASH
I BOYS
ISBN 978-O-393-24466-3
USA $27.95
CAN. $32.95
Four years after his #1 bestseller The Big
Short , Michael Lewis returns to Wall Stree c
report on a high-tech predator stalking the
equity markets.
Flash Boys is about a small group of Wall
Street guys who figure out that the U.S. stock
market has been rigged for the benefit of
insiders and that, post-financial crisis, the
markets have become not more free but less,
and more controlled by the big Wall Street
banks. Working at different firms, they come
to this realization separately; but after they
discover one another, the flash boys band
together and set out to reform the financial
markets. This they do by creating an exchange
in which high-frequency trading — source of
the most intractable problems — will have no
advantage whatsoever.
The characters in Flash Boys are fabulous,
each completely different from what you
think of when you think “Wall Street guy.”
Several have walked away from jobs in the
financial sector that paid them millions of
dollars a year. From their new vantage point
they investigate the big banks, the world’s
stock exchanges, and high-frequency trading
firms as they have never been investigated,
and expose the many strange new ways that
Wall Street generates profits.
The light that Lewis shines into the darkes’
corners of the financial world may not be
(continued on back flap)
APR 2014
FLASH
BOYS
ALSO BY MICHAEL LEWIS
Boomerang
The Big Short
Home Game
The Blind Side
Coach
Moneyball
Next
The Neu> New Thing
Losers
Pacific Rift
The Money Culture
Liar’s Poker
EDITED BY MICHAEL LEWIS
Panic
MICHAEL LEWIS
FLASH
BOYS
A WALL STREET REVOLT
W. W. NORTON & COMPANY
New York | London
Copyright © 2014 by Michael Lewis
All rights reserved
Printed in the United States of America
First Edition
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1234567890
A man got to have a code.
— Omar Little
CONTENTS
INTRODUCTION
CHAPTER 1
CHAPTER 2
CHAPTER 3
CHAPTER 4
CHAPTER 5
CHAPTER 6
CHAPTER 7
CHAPTER 8
EPILOGUE
WINDOWS ON THE WORLD 1
HIDDEN IN PLAIN SIGHT 7
BRAD’S PROBLEM 23
RONAN’S PROBLEM 56
TRACKING THE PREDATOR 89
PUTTING A FACE ON HFT 128
HOW TO TAKE BILLIONS FROM
WALL STREET 151
AN ARMY OF ONE 193
THE SPIDER AND THE FLY 244
RIDING THE WALL STREET TRAIL
Acknowledgments 273
FLASH
BOYS
INTRODUCTION
WINDOWS
ON THE WORLD
I suppose this book started when I first heard the story ot Ser-
gey Aleynikov, the Russian computer programmer who had
worked for Goldman Sachs and then, in the summer of 2009,
after he’d quit his job, was arrested by the FBI and charged by
the United States government with stealing Goldman Sachs’s
computer code. I’d thought it strange, after the financial crisis,
in which Goldman had played such an important role, that the
only Goldman Sachs employee who had been charged with any
sort of crime was the employee who had taken something from
Goldman Sachs. I’d thought it even stranger that government
prosecutors had argued that the Russian shouldn’t be freed on
bail because the Goldman Sachs computer code, in the wrong
hands, could be used to “manipulate markets in unfair ways.”
(Goldman’s were the right hands? If Goldman Sachs was able to
manipulate markets, could other banks do it, too?) But maybe
the strangest aspect of the case was how difficult it appeared to
be — for the few who attempted — to explain what the Russian
2
FLASH BOYS
had done. I don’t mean only what he had done wrong: I mean
what he had done. His job. He was usually described as a “high-
frequency trading programmer,” but that wasn’t an explanation.
That was a term of art that, in the summer of 2009, most people,
even on Wall Street, had never before heard. What was high-
frequency trading? Why was the code that enabled Goldman
Sachs to do it so important that, when it was discovered to have
been copied by some employee, Goldman Sachs needed to call
the FBL It this code was at once so incredibly valuable and so
dangerous to financial markets, how did a Russian who had
worked for Goldman Sachs for a mere two years get his hands
on it?
At some point I went looking for someone who might answer
those questions. My search ended in a room looking out at the
World Trade Center site, at One Liberty Plaza. In this room
were gathered a small army of shockingly well-informed people
from every corner ot Wall Street — big banks, the major stock
exchanges, and high-frequency trading firms. Many of them had
left high-payingjobs to declare war on Wall Street, which meant,
among other things, attacking the very problem that the Russian
computer programmer had been hired by Goldman Sachs to
create. In the bargain they’d become experts on the questions
I sought answers to, along with a lot of other questions I hadn’t
thought to ask. These, it turned out, were tar more interesting
than I expected them to be.
I didn t start out with much interest in the stock market —
though, like most people, I enjoy watching it go boom and crash.
When it crashed on October 19, 1987, I happened to be hovering
around the fortieth floor of One New York Plaza, the stock market
trading and sales department of my then employer, Salomon
Brothers. That was interesting. If you ever needed proof that even
WINDOWS ON THE WORLD
3
Wall Street insiders have no idea what’s going to happen next on
Wall Street, there it was. One moment all is well; the next, the
value of the entire U.S. stock market has fallen 22.61 percent, and
no one knows why. During the crash, some Wall Street brokers,
to avoid the orders their customers wanted to place to sell stocks,
simply declined to pick up their phones. It wasn’t the first time
that Wall Street people had discredited themselves, but this time
the authorities responded by changing the rules — making it easier
for computers to do the jobs done by those imperfect people. The
1987 stock market crash set in motion a process — weak at first,
stronger over the years — that has ended with computers entirely
replacing the people.
Over the past decade, the financial markets have changed too
rapidly for our mental picture of them to remain true to lite. The
picture I’ll bet most people have of the markets is still a picture a
human being might have taken. In it, a ticker tape runs across the
bottom of some cable TV screen, and alpha males in color-coded
jackets stand in trading pits, hollering at each other. That picture
is dated; the world it depicts is dead. Since about 2007, there
have been no thick-necked guys in color-coded jackets standing
in trading pits; or, if they are, they’re pointless. There are still
some human beings working on the floor of the New York Stock
Exchange and the various Chicago exchanges, but they no longer
preside over any financial market or have a privileged view inside
those markets. The U.S. stock market now trades inside black
boxes, in heavily guarded buildings in New Jersey and Chicago.
What goes on inside those black boxes is hard to say — the ticker
tape that runs across the bottom of cable TV screens captures
only the tiniest fraction of what occurs in the stock markets. The
public reports of what happens inside the black boxes are fuzzy
and unreliable — even an expert cannot say what exactly happens
4
FLASH BOYS
inside them, or when it happens, or why. The average investor has
no hope of knowing, of course, even the little he needs to know.
He logs onto his TD Ameritrade or E*Trade or Schwab account,
enters a ticker symbol of some stock, and clicks an icon that says
“Buy”: Then what? He may think he knows what happens after
he presses the key on his computer keyboard, but, trust me, he
does not. If he did, he’d think twice before he pressed it.
The world clings to its old mental picture of the stock market
because it’s comforting; because it’s so hard to draw a picture of
what has replaced it; and because the few people able to draw it
for you have no interest in doing so. This book is an attempt to
draw that picture. The picture is built up from a bunch of smaller
pictures — of post-crisis Wall Street; of new kinds of financial
cleverness; of computers, programmed to behave impersonally in
ways that the programmer himself would never do personally; of
people, coming to Wall Street with one idea of what makes the
place tick only to find that it ticks rather differently than they had
supposed. One of these people — a Canadian, of all things — stands
at the picture’s center, organizing the many smaller pictures into
a coherent whole. His willingness to throw open a window on
the American financial world, and to show people what it has
become, still takes my breath away.
As does the Goldman high-frequency trading programmer
arrested for stealing Goldman’s computer code. When he worked
for Goldman Sachs, Sergey Aleynikov had a desk on the forty-
second floor of One New York Plaza, the site of the old Salomon
Brothers trading floor, two floors above the place I’d once watched
the stock market crash. He hadn’t been any more interested in
staying in that building than 1 had been and, in the summer of
2009, had left to seek his fortune elsewhere. On July 3, 2009, he
was on a flight from Chicago to Newark, New Jersey, blissfully
WINDOWS ON THE WORLD
5
unaware of his place in the world. He had no way of knowing
what was about to happen to him when he landed. Then again,
he had no idea how high the stakes had become in the financial
game he’d been helping Goldman Sachs to play. Oddly enough,
to see the magnitude of those stakes, he had only to look out the
window of his airplane, down on the American landscape below.
CHAPTER ONE
HIDDEN IN PLAIN SIGHT
B y the summer of 2009 the line had a life of its own, and two
thousand men were digging and boring the strange home
it needed to survive. Two hundred and five crews of eight
men each, plus assorted advisors and inspectors, were now rising
early to figure out how to blast a hole through some innocent
mountain, or tunnel under some riverbed, or dig a trench beside
a country road that lacked a roadside- — all without ever answering
the obvious question: Why? The line was just a one-and-a-half-
inch-wide hard black plastic tube designed to shelter four hundred
hair-thin strands of glass, but it already had the feeling of a living
creature, a subterranean reptile, with its peculiar needs and wants.
It needed its burrow to be straight, maybe the most insistently
straight path ever dug into the earth. It needed to connect a data
center on the South Side of Chicago* to a stock exchange in north-
ern New Jersey. Above all, apparently, it needed to be a secret.
The principal data center was later moved to Aurora, Illinois, outside Chicago.
8
FLASH BOYS
The workers were told only what they needed to know. They
tunneled in small groups apart from each other, with only a
local sense ot where the line was coming from or where it was
going to. They were specifically not told of the line’s purpose —
to make sure they didn’t reveal that purpose to others. “All the
time, people are asking us, ‘Is this top secret? Is it the govern-
ment? I just said, Yeah, ’ said one worker. The workers might
not have known what the line was for, but they knew that it had
enemies: They all knew to be alert to potential threats. If they
saw anyone digging near the line, for instance, or noticed any-
one asking a lot of questions about it, they were to report what
they’d seen immediately to the head office. Otherwise they were
to say as little as possible. If people asked them what they were
doing, they were to say, “Just laying fiber.” That usually ended
the conversation, but if it didn’t, it didn’t really matter. The con-
struction crews were as bewildered as anyone. They were used
to digging tunnels that connected cities to other cities, and peo-
ple to other people. This line didn’t connect anyone to anyone
else. Its sole purpose, as far as they could see, was to be as straight
as possible, even if that meant they had to rocksaw through a
mountain rather than take the obvious way around it. Why?
Right up until the end, most workers didn’t even ask the
question. The country was flirting with another depression and
they were just happy for the work. As Dan Spivey said, “No one
knew why. People began to make their reasons up.”
Spivey was the closest thing the workers had to an explanation
for the line, or the bed they were digging for it. And Spivey was
by nature tight-lipped, one of those circumspect southerners with
more thoughts than he cared to share. He’d been born and raised
in Jackson, Mississippi, and, on those rare occasions he spoke, he
sounded as if he d never left. He’d just turned forty but was still as
HIDDEN IN PLAIN SIGHT
9
lean as a teenager, with the face of a Walker Evans tenant farmer.
After some unsatisfying years working as a stockbroker in Jack-
son he’d quit, as he put it, “to do something more sporting.” That
turned out to be renting a seat on the Chicago Board Options
Exchange and making markets for his own account. Like every
other trader on the Chicago exchanges, he saw how much money
could be made trading futures contracts in Chicago against the
present prices of the individual stocks trading in New York and
New Jersey. Every day there were thousands of moments when
the prices were out of whack — when, for instance you could sell
the futures contract for more than the price of the stocks that
comprised it. To capture the profits, you had to be fast to both
markets at once. What was meant by “fast” was changing rapidly.
In the old days — before, say, 2007 — the speed with which a trader
could execute had human limits. Human beings worked on the
floors of the exchanges, and if you wanted to buy or sell anything
you had to pass through them. The exchanges, by 2007, were
simply stacks of computers in data centers. The speed with which
trades occurred on them was no longer constrained by people.
The only constraint was how fast an electronic signal could travel
between Chicago and New York — or, more precisely, between
the data center in Chicago that housed the Chicago Mercantile
Exchange and a data center beside the Nasdaq’s stock exchange
in Carteret, New Jersey.
What Spivey had realized, by 2008, was that there was a big
difference between the trading speed that was available between
these exchanges and the trading speed that was theoretically pos-
sible. Given the speed of light in fiber, it should have been pos-
sible for a trader who needed to trade in both places at once to
send his order from Chicago to New York and back in roughly
12 milliseconds, or roughly a tenth of the time it takes you to
10
FLASH BOYS
blink your eyes, if you blink as fast as you can. (A millisecond
is one thousandth of a second.) The routes offered by the vari-
ous telecom carriers — Verizon, AT&T, Level 3, and so on — were
slower than that, and inconsistent. One day it took them 17 mil-
liseconds to send an order to both data centers; the next, it took
them 16 milliseconds. By accident, some traders had stumbled
across a route controlled by Verizon that took 14.65 milliseconds.
“The Gold Route,” the traders called it, because on the occasions
you happened to find yourself on it you were the first to exploit
the discrepancies between prices in Chicago and prices in New
York. Incredibly to Spivey, the telecom carriers were not set up
to understand the new demand for speed. Not only did Verizon
fail to see that it could sell its special route to traders for a fortune;
Verizon didn’t even seem aware it owned anything of special
value. “You would have to order up several lines and hope that
you got it,” says Spivey. “They didn’t know what they had.” As
late as 2008, major telecom carriers were unaware that the finan-
cial markets had changed, radically, the value of a millisecond.
Upon closer investigation, Spivey saw why. He went to Wash-
ington, DC, and got his hands on the maps of the existing fiber
cable routes running from Chicago to New York. They mostly
followed the railroads and traveled from big city to big city.
Leaving New York and Chicago, they ran fairly straight toward
each other, but when they reached Pennsylvania they began to
wiggle and bend. Spivey studied a map of Pennsylvania and saw
the main problem: the Allegheny Mountains. The only straight
line running through the Alleghenies was the interstate high-
way, and there was a law against laying fiber along the interstate
highway. The other roads and railroads zigzagged across the state
as the landscape permitted. Spivey found a more detailed map of
Pennsylvania and drew his own line across it. “The straightest
HIDDEN IN PLAIN SIGHT
11
path allowed by law,” he liked to call it. By using small paved
roads and dirt roads and bridges and railroads, along with the
occasional private parking lot or front yard or cornfield, he
could cut more than a hundred miles oft the distance traveled by
the telecom carriers. What was to become Spivey’s plan, then his
obsession, began with an innocent thought: I’d like to see how
much faster someone would be if they did this.
In late 2008, with the global financial system in turmoil,
Spivey traveled to Pennsylvania and found a construction guy
to drive him the length of his idealized route. For two days they
rose together at five in the morning and drove until seven at
night. “What you see when you do this,” says Spivey, “is very
small towns, and very tiny roads with cliffs on one side and a
sheer rock wall on the other.” The railroads traveling east to
west tended to tack north and south to avoid the mountains:
They were of limited use. “Anything that wasn’t absolutely east-
west that had any kind of curve in it I didn’t like,” Spivey said.
Small country roads were better for his purposes, but so tightly
squeezed into the rough terrain that there was no place to lay the
fiber but under the road. “You’d have to close the road to dig up
the road,” he said.
The construction guy with him clearly suspected he might be
out of his mind. Yet when Spivey pressed him, even he couldn’t
come up with a reason why the plan wasn’t at least theoretically
possible. That’s what Spivey had been after: a reason not to do
it. “I was just trying to find the reason no [telecom] carrier had
done it,” he says. “I was thinking: Surely I’ll see some road-
block.” Aside from the construction engineer’s opinion that no
one in his right mind wanted to cut through the hard Allegheny
rock, he couldn’t find one.
That’s when, as he puts it, “I decided to cross the line.” The
12
FLASH BOYS
line separated Wall Street guys who traded options on Chicago
exchanges from people who worked in the county agencies and
Department of Transportation offices that controlled public
rights-of-way through which a private citizen might dig a secret
tunnel. He sought answers to questions: What were the rules
about laying fiber-optic cable? Whose permission did you need?
The line also separated Wall Street people from people who
knew how to dig holes and lay fiber. How long would it take?
How many yards a day might a crew with the right equipment
tunnel through rock? What kind of equipment was required?
What might it cost?
Soon a construction engineer named Steve Williams, who
lived in Austin, Texas, received an unexpected call. As Williams
recalls, “It was from a friend of mine. He said, ‘I have an old
friend whose cousin is in trouble, and he has some construc-
tion questions he needs answers to.’ ” Spivey himself then called.
“This guy gets on the phone,” recalls Williams, “and is ask-
ing questions about case sizes, and what kind of fiber you use,
and how would you dig in this ground and under this river.”
A few months later Spivey called him again — to ask him if he
would supervise the laying of a fifty-mile stretch of fiber, start-
ing in Cleveland. “I didn’t know what I was getting into,” said
Williams. Spivey told him nothing more about the project than
what he needed to know to lay a single fifty-mile stretch of
cable. In between, Spivey had persuaded Jim Barskdale, the for-
mer CEO of Netscape Communications and a fellow native of
Jackson, to fund what Spivey estimated to be a $300 million
tunnel. They named the company Spread Networks, though
they disguised the construction behind shell companies with
dull names like Northeastern ITS and Job 8. Jim Barksdale’s son,
David Barksdale, came on board — to cut, as quietly as possible,
HIDDEN IN PLAIN SIGHT
13
the four hundred or so deals they needed to cut with townships
and counties in order to be able to tunnel through them. Wil-
liams then proved so adept at getting the line into the ground
that Spivey and Barksdale called and asked him to take over the
entire project. “That’s when they said, ‘Hey, this is going all the
way to New Jersey,’ ” Williams said.
Leaving Chicago, the crews had raced across Indiana and
Ohio. On a good day they were able to lay two to three miles of
the line in the ground. When they arrived in western Pennsyl-
vania they hit the rock and the pace slowed, sometimes to a few
hundred feet a day. “They call it blue rock,” says Williams. “It’s
hard limestone. And it’s a challenge to get through.” He found
himself having the same conversation, over and over again, with
Pennsylvania construction crews. “I’d explain to them that we
need to go through some mountain, and one after another they
would say, ‘That’s crazy.’ And I would say, ‘I know that’s crazy,
but that’s how we’re doing it.’ And they would ask, ‘Why?’ And
I’d say, ‘It’s more of a customized route to the owner’s wishes.’ ”
To which they really didn’t have much to say except, “Oh.”
His other problem was Spivey, who was all over him about the
slightest detours. For instance, every so often the right-of-way
crossed over from one side of the road to the other, and the line
needed to cross the road within its boundaries. These constant
road crossings irritated Spivey — Williams was making sharp
right and left turns. “Steve, you’re costing me a hundred nano-
seconds,” he’d say. (A nanosecond is one billionth of one sec-
ond.) And: “Can you at least cross it diagonally ?”
Spivey was a worrier. He thought that when a person took
risks, the thing that went wrong was usually a thing the person
hadn’t thought about, and so he tried to think about the things he
wouldn’t naturally think about. The Chicago Mercantile Exchange
14
FLASH BOYS
might dose and move to New Jersey. The Calumet River might
prove impassable. Some company with deep pockets — a big Wall
Street bank, a telecom carrier — might discover what he was
doing and do it themselves. That last fear — that someone else was
already out there, digging Ins own straight tunnel — consumed
him. Every construction person he talked to thought he was out
of his mind, and yet he was sure the Alleghenies were crawl-
ing with people who shared his obsession. “When something
becomes obvious to you,” he said, “you immediately think
surely someone else is doing this.”
What never crossed his mind was that, once his line was fin-
ished, Wall Street would not want to buy the line. Just the reverse:
He assumed that the line would be the site of a gold rush. Maybe
for that reason, he and his backers hadn’t thought much about
how to sell the line until the time came to do it. It was compli-
cated. What they were selling — speed — was only valuable to the
extent that it was scarce. What they did not know was the degree
of scarcity that would maximize the line’s market value. How
much was it worth to a single player in the U.S. stock market to
have an advantage in speed over everyone else? How much to
twenty-five different players — to share the same advantage over
the rest of the market? To answer these sorts of questions, it helps
to know how much money traders can make purely from speed
in the U.S. stock market, and how, exactly, they make it. “No
one knew this market,” says Spivey. “It was opaque.”
They considered holding a Dutch auction — that is, start at
some high reserve price and lower it until the line was bought by
a single Wall Street firm, which would then enjoy a monopoly.
They weren’t confident that any one bank or hedge fund would
fork over the many billions of dollars they assumed the monop-
oly was worth, and they didn’t like the sound of the inevitable
HIDDEN IN PLAIN SIGHT
15
headlines in the newspapers: Barksdale Makes Billions Sell-
ing Out Ordinary American Investor. They hired an industry
consultant named Larry Tabb, who had caught Jim Barksdale’s
attention with a paper he’d written called “The Value of a Milli-
second.” One way to price access to the line, Tabb thought, was
to figure out how much money might be made from it, from the
so-called spread trade between New York and Chicago — the
simple arbitrage between cash and futures. Tabb estimated that
if a single Wall Street bank were to exploit the countless minus-
cule discrepancies in price between Thing A in Chicago and
Thing A in New York, they’d make profits of $20 billion a year.
He further estimated that there were as many as four hundred
firms then vying to capture the $20 billion. All of them would
need to be on the fastest line between the two cities — and there
were only places for two hundred of them on the line.
Both estimates happily coincided with Spivey’s sense of the
market, and he took to saying, with obvious pleasure, “We have
two hundred shovels for four hundred ditch diggers.” But what
to charge for each shovel? “It was really a total wet finger in the
air,” says Brennan Carley, who had worked closely with a lot of
high-speed traders, and who had been hired by Spivey to sell his
network to them. “All of us were just guessing.” The number
they came up with was $300,000 a month, roughly ten times the
price of the existing telecom lines. The first two hundred stock
market players willing to pay in advance and sign a five-year
lease would get a deal: $10.6 million for five years. The traders
who leased Spread’s line would also need to buy and maintain
their own signal amplifiers, housed in thirteen amp sites along
Spread’s route. All-in, the up-front cost to each of the two hun-
dred traders would come to about $14 million, or a grand total
of $2.8 billion.
16
FLASH BOYS
By early 2010 Spread Networks still hadn’t informed a single
prospective customer of their existence. A year after the work-
ers had started digging, the line was, incredibly, still a secret.
To maximize the line’s shock value and minimize the chance
that someone else would seek to replicate what they had done,
or even announce their intention to do so, they decided to wait
until March 2010, three months before the line was due to be
completed, before they tried to sell it. How to approach the rich
and powerful men whose businesses they were about to disrupt?
“The general modus operandi was to find someone at one of
these firms one of us knew,” says Brennan Carley. “We’d say,
‘You know me. You know ofjim Barksdale. We have something
we want to come over and talk to you about. We can’t tell you
what it is until we get there. And, by the way, we want you to
sign an NDA [non-disclosure agreement] before we come in.’ ”
That’s how they went to Wall Street — in stealth. “There were
CEOs at every meeting,” says Spivey. The men with whom they
met were among the most highly paid people in the financial
markets. The first reaction of most of them was total disbelief.
“People told me later that they thought, Surely not, but let’s
talk to him anyway,” says Spivey. Anticipating their skepticism,
he carried with him a map, four feet by eight feet. He finger-
walked them through his cross-country tunnel. Even then peo-
ple still demanded proof. You couldn’t actually see a fiber-optic
line buried three feet under the ground, but the amp sites were
highly visible thousand-square-foot concrete bunkers. Light
fades as it travels; the fainter it becomes, the less capable it is
of transmitting data. The signals transmitted from Chicago to
New Jersey needed to be amplified every fifty to seventy-five
miles, and for the amplifiers that did the work, Spread had built
these maximum-security bunkers along the route. “I know you
HIDDEN IN PLAIN SIGHT
17
guys are straight shooters,” one trader said to them. “But I never
heard of you before. I want to see a picture of this place.” Every
day for the next three months, Spivey emailed this man a pho-
tograph of the most recent amp site under construction to show
him that it was actually being built.
Once their disbelief faded, most of the Wall Street guys were
just in awe. Of course they all still asked the usual questions.
What do I get for my $14 million in assorted fees and expenses? (Two
glass fibers, one for each direction.) What happens if the line’s cut
by a backhoe ? (We have people on the line who will have it up
and running in eight hours.) Where is the backup if your line goes
doum? (Sorry, there isn’t one.) When can you supply us with the five
years of audited financial statements that we require before we do busi-
ness with any firm? (Um, in five years.) But even as they asked
their questions and ticked their boxes, they failed to disguise
their wonder. Spivey’s favorite meeting was with a trader who
sat stone-faced listening to him for fifteen minutes on the other
side of a long conference table, then leapt to his feet and shouted,
“SHIT, THIS IS COOL!”
In these meetings what didn’t get said was often as interest-
ing as what did. The financial markets were changing in ways
even professionals did not fully understand. Their new ability
to move at computer, rather than human, speed had given rise
to a new class of Wall Street traders, engaged in new kinds of
trading. People and firms no one had ever heard of were get-
ting very rich very quickly without having to explain who they
were or how they were making their money: These people were
Spread Networks’ target audience. Spivey actually didn’t care
to pry into their warring trading strategies. “We never wanted
to come across as if we knew how they were making money on
this,” he said. He didn’t ask, they didn’t say. But the response of
18
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many ot them suggested that their entire commercial existence
depended on being faster than the rest of the stock market —
and that whatever they were doing wasn’t as simple as the age-
old cash to futures arbitrage. Some of them, as Brennan Carley
put it, “would sell their grandmothers for a microsecond.” (A
microsecond is one millionth of a second.) Exactly why speed
was so important to them was not clear; what was clear was that
they felt threatened by this faster new line. “Somebody would
say, ‘Wait a second,’ ” recalls Carley. “ ‘If we want to continue
with the strategies we are currently running, we have to be on
this line. We have no choice but to pay whatever you’re ask-
ing. And you’re going to go from my office to talk to all of my
competitors.’ ”
“I’ll tell you my reaction to them,” says Darren Mulholland,
a principal at a high-speed trading firm called Hudson River
Trading. “It was, ‘Get out of my office.’ The thing I couldn’t
believe was that when they came to my office they were going
to go live in a month. And they didn’t even know who the cli-
ents were! They only discovered us from reading a letter we’d
written to the SEC. . . .Who takes those kinds of business risks?”
For $300,000 a month plus a few million more in up-front
expenses, the people on Wall Street then making perhaps more
money than people have ever made on Wall Street would enjoy
the right to continue doing what they were already doing. “At
that point they’d get kind of pissed off,” says Carley. After one
sales meeting, David Barksdale turned to Spivey and said, Those
people hate us. Oddly enough, Spivey loved these hostile encoun-
ters. “It was good to have twelve guys on the other side of the
table, and they are all mad at you,” he said. “A dozen people told
us only four guys would buy it, and they all bought it.” (Hudson
River Trading bought the line.) Brennan Carley said, “We used
HIDDEN IN PLAIN SIGHT
19
to say, ‘We can’t take Dan to this meeting, because even if they
have no choice, people do not want to do business with people
they’re angry with.’ ”
When the salesmen from Spread Networks moved from the
smaller, lesser-known Wall Street firms to the big banks, the view
inside the post-crisis financial world became even more intrigu-
ing. Citigroup, weirdly, insisted that Spread reroute the line from
the building next to the Nasdaq in Carteret to their offices in
lower Manhattan, the twists and turns of which added several
milliseconds and defeated the line’s entire purpose. The other
banks all grasped the point of the line but were given pause by
the contract Spread required them to sign. This contract pro-
hibited anyone who leased the line from allowing others to use
it. Any big bank that leased a place on the line could use it for
its own proprietary trading but was forbidden from sharing it
with its brokerage customers. To Spread this seemed an obvious
restriction: The line was more valuable the fewer people that
had access to it. The whole point of the line was to create inside
the public markets a private space, accessible only to those will-
ing to pay the tens of millions of dollars in entry fees. “Credit
Suisse was outraged,” says a Spread employee who negotiated
with the big Wall Street banks. “They said, ‘You’re enabling
people to screw their customers.’ ” The employee tried to argue
that this was not true — that it was more complicated than that —
but in the end Credit Suisse refused to sign the contract. Morgan
Stanley, on the other hand, came back to Spread and said, We
need you to change the language. “We say, ‘But you’re okay with
the restrictions?’ And they say, ‘Absolutely, this is totally about
optics.’ We had to wordsmith it so they had plausible deniabil-
ity.” Morgan Stanley wanted to be able to trade for itself in a way
it could not trade for its customers; it just didn’t want to seem as
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if it wanted to. Of all the big Wall Street banks, Goldman Sachs
was the easiest to deal with. “Goldman had no problem signing
it,” the Spread employee said.
It was at just this moment — as the biggest Wall Street banks
were leaping onto the line — that the line stopped in its tracks.
There’d been challenges all along the route. After leaving
Chicago they had tried and failed six times to tunnel 120 feet
under the Calumet River. They were about to give up and find
a slower way around when they stumbled upon a century-old
tunnel that hadn’t been used in forty years. The first amp site
after leaving Carteret was supposed to be near a mall in Alpha,
New Jersey. The guy who owned the land said no. “He said he
knew it was going to be some kind of terrorist target and he
didn’t want it in the neighborhood,” said Spivey. “There’s always
little gotchas out there that you have to be careful of.”
Pennsylvania had proved even more difficult than Spivey had
imagined. Coming from the east, the line ran to a small forest in
Sunbury, just off the east bank of the Susquehanna River, where
it stopped and waited for its western twin. The line coming from
the west needed to cross the Susquehanna. That stretch of river
was breathtakingly wide. There was one drill in the world — it
would cost them $2 million to rent — capable of boring a tunnel
under the river. In June 2010, the drill was in Brazil. “We need
a drill that is in Brazil ,” says Spivey. “That idea is quite alarm-
ing. Obviously someone is using the drill. When do we get to
use it?” At the last minute they overcame some objections from
Pennsylvania bridge authorities and were permitted to cross the
river on the bridge — by boring holes through its concrete pylons
and running the cable on the underside of the bridge.
At which point the technical problems gave way to social
problems. Leaving the bridge, the road split; one branch went
HIDDEN IN PLAIN SIGHT
21
north; the other, south. If you attempted to travel due east, you
hit a dead end. The readjust stopped, near a sign beside a levee
that said, Welcome to Sunbury. Blocking the line’s path were
two big parking lots. One belonged to a company that manufac-
tured wire rope, the cable used on ski lifts; the other was owned
by a century-old grocery store named Weis Markets. To reach
its twin in the Sunbury forest, the line needed to pass through
one of these parking lots or travel around the entire city. The
owners of both Weis Markets and the Wirerope Works were
hostile or suspicious, or both; they weren’t returning calls. “The
whole state has been abused by coal companies,” Steve Wil-
liams explained. “When you say you want to dig, everyone gets
suspicious.”
Going around rather than through the town, Spivey calcu-
lated, would cost several months and a lot of money and would
add four microseconds to his route. It would also prevent Spread
Networks from delivering the cable on time to the Wall Street
banks and traders ready to write checks for $10.6 million for it.
But the guy who ran the wire rope factory was for some reason
so angry with Spread’s local contractor that he wouldn’t speak
to them. The guy who ran the Weis Markets was even harder
to reach. His secretary told Spread that he was at a golf tourna-
ment, and unavailable. He’d already decided — without inform-
ing Spread Networks — to reject the somewhat strange offer of
low six figures plus free high-speed Internet access they had
offered him in exchange for a ten-foot easement under his park-
ing lot. The line passed too close to his ice cream-making plant.
The chairman had no interest in signing over a permanent ease-
ment that would make it difficult to expand the ice cream plant.
In July 2010 the line dropped back underground beneath the
bridge in Sunbury and just stopped. “We had all this fiber out
22
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there and we needed it to talk to each other and it couldn’t,”
said Spivey. Then, for some reason he never fully understood,
the wire rope people softened. They sold him the easement he
needed. The day after Spread Networks acquired lifetime rights
to a ten-foot-wide path under the wire rope factory’s parking
lot, it sent out its first press release: “Round-trip travel time from
Chicago to Newjersey has been cut to 13 milliseconds.” They’d
set a goal of coming in at under 840 miles and beaten it; the line
was 827 miles long. “It was the biggest what-the-fuck moment
the industry had had in some time,” said Spivey.
Even then, none of the line’s creators knew for sure how
the line would be used. The biggest question about the line —
Why ? — remained imperfectly explored. All its creators knew
was that the Wall Street people who wanted it wanted it very
badly — and also wanted to find ways for others not to have it.
In one of his first meetings with a big Wall Street firm, Spivey
had told the firm’s boss the price of his line: $10.6 million plus
costs if he paid up front, $20 million or so if he paid in install-
ments. The boss said he’d like to go away and think about it. He
returned with a single question: “Can you double the price?”
CHAPTER TWO
BRAD’S PROBLEM
U p till the moment of the collapse of the U.S. financial
system, Brad Katsuyama could tell himself that he bore
no responsibility for that system. He worked for the
Royal Bank of Canada, for a start. RBC might be the ninth
biggest bank in the world, but it was on no one’s mental map of
Wall Street. It was stable and relatively virtuous, and soon to be
known for having resisted the temptation to make bad subprime
loans to Americans or peddle them to ignorant investors. But its
management didn’t understand just what an afterthought their
bank was — on the rare occasions American financiers thought
about them at all. Brad’s bosses had sent him from Toronto to
New York back in 2002, when he was twenty-four years old, as
part of a “big push” to become a player on Wall Street. The sad
truth about the big push was that hardly anyone noticed it. As a
trader who moved to RBC from Morgan Stanley put it, “When
I got there, it was like, ‘Holy shit, welcome to the small time!’ ”
Brad himselt said, “7’he people in Canada are always saying,
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‘We’re paying too much for people in the United States.’ What
they don’t realize is that the reason you have to pay them too
much is that no one wants to work for RBC. RBC is a nobody.”
It was as if the Canadians had summoned the nerve to audition
for a role in the school play, then turned up for it wearing a car-
rot costume.
Before they sent him there to be part of the big push, Brad
had never laid eyes on Wall Street or New York City. It was his
first immersive course in the American way of life, and he was
instantly struck by how different it was from the Canadian ver-
sion. “Everything was to excess,” he said. “I met more offensive
people in a year than I had in my entire life. People lived beyond
their means, and the way they did it was by going into debt.
That’s what shocked me the most. Debt was a foreign concept in
Canada. Debt was evil. I’d never been in debt in my life, ever. I
got here and a real estate broker said, ‘Based on what you make,
you can afford a $2.5 million apartment.’ I was like, What the
fuck are you talking about?” In America, even the homeless were
profligate. Back in Toronto, after a big bank dinner, Brad would
gather the leftovers into covered tin trays and carry them out to a
homeless guy he saw every day on his way to work. The guy was
always appreciative. When the bank moved him to New York,
he saw more homeless people in a day than he saw back home
in a year. When no one was watching, he’d pack up the king’s
banquet of untouched leftovers after the New York lunches and
walk it down to the people on the streets. “They just looked at
me like, ‘What the fuck is this guy doing?’ ” he said. “I stopped
doing it because I didn’t feel like anyone gave a shit.”
In the United States, Brad also noticed, he was expected to
accept distinctions between himself and others that he’d simply
ignored in Canada. Growing up, he’d been one of the very few
BRAD’S PROBLEM
25
Asian kids in a white suburb of Toronto. During World War II,
his Japanese Canadian grandparents had been interned in prison
camps in western Canada. Brad never mentioned this or any-
thing else having to do with race to his friends, and they ended
up thinking of him almost as a person who did not have a racial
identity. His genuine lack of interest in the subject became an
issue only after he arrived in New York. Worried that it needed
to do more to promote diversity, RBC invited Brad along with
a bunch of other nonwhite people to a meeting to discuss the
issue. Going around the table, people took turns responding to
a request to “talk about your experience of being a minority at
RBC.” When Brad’s turn came he said, “To be honest, the only
time I’ve ever felt like a minority is this exact moment. If you
really want to encourage diversity you shouldn’t make people
feel like a minority.” Then he left. The group continued to meet
without him.
The episode said as much about him as it did about his new
home. Ever since he was a little kid, more by instinct than con-
scious thought, he had resisted the forces that sought to separate
him from any group to which he felt he belonged. When he
was seven his mother told him he’d been identified as a gifted
student, and she offered him the chance to attend special school.
He told her he wanted to stay with his friends and attend the
normal school. In high school the track coach thought he could
be a star (he ran a 4.5-second forty-yard dash), until he told the
coach that he’d rather play a team sport — he stuck with hockey
and football. Upon leaving high school at the top of his class, he
could have gone on scholarship to any university in the world:
He was not only the best student but a college-caliber tailback
and a talented pianist. Instead he chose to follow his girlfriend
and his football teammates to Wilfrid Laurier University, an
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hour or so from Toronto. After he graduated from Laurier, tak-
ing the prize for best student in the business program, he wound
up trading stocks at the Royal Bank of Canada — not because he
had any particular interest in the stock market but because he had
no idea what else to do for a living. Up till the moment he was
forced to, he hadn’t really thought about what he wanted to be
when he grew up, or that he might end up in some radically dif-
ferent place than the friends he’d grown up with. What he liked
about the RBC trading floor, aside from the feeling it gave him
that it would reward his analytical abilities, was that it reminded
him of a locker room. Another group, to which he naturally
belonged.
The RBC trading floor at One Liberty Plaza looked out on
the holes once filled by the Twin Towers. When Brad arrived,
the firm was still conducting air quality studies to determine if
it was safe for its employees to breathe. In time they just sort of
forgot about what had happened in this place; the hole in the
ground became the view you looked at without ever seeing it.
For his first few years on Wall Street, Brad traded U.S. tech
and energy stocks. He had some fairly abstruse ideas about how
to create what he called “perfect markets,” and they worked so
well that he was promoted to run the equity trading depart-
ment, consisting of twenty or so traders. The RBC trading floor
had what the staff liked to refer to as a “no-asshole rule”; if
someone came in the door looking for a job and sounding like
a typical Wall Street asshole, they wouldn’t hire him, no matter
how much money he said he could make the firm. There was
even an expression used to describe the culture: “RBC nice.”
Although Brad found the expression embarrassingly Canadian,
he, too, was RBC nice. The best way to manage people, he
thought, was to convince them that you were good for their
BRAD’S PROBLEM
27
careers. He further believed that the only way to get people to
believe that you were good for their careers was actually to be
good for their careers. These thoughts came naturally to him:
They just seemed obvious.
If there was a contradiction between who Brad Katsuyama
was and what he did for a living, he didn’t see it. He assumed he
could be a trader on Wall Street without its having the slightest
effect on his habits, tastes, worldview, or character. And during
his first few years on Wall Street he appeared to be correct. Just
by being himself he became, on Wall Street, a great success.
“His identity at RBC in New York was very simple,” says a
former colleague. “Brad was the golden child. People thought
he was going to end up running the bank.” For more or less his
entire life, Brad Katsuyama had trusted the system; and the sys-
tem, in return, trusted Brad Katsuyama. That left him especially
unprepared for what the system was to do to him.
HIS TROUBLES BEGAN at the end of 2006, after RBC paid $100
million for a U.S. electronic stock market trading firm called
Carlin Financial. In what appeared to Brad to be undue haste,
his bosses back in Canada bought Carlin without knowing much
about either it or electronic trading. In what he thought to be
typical Canadian fashion, they had been slow to react to a big
change in the financial markets; but once they felt compelled to
act, they’d panicked. “The bank’s run by these Canadian guys
from Canada,” a former RBC director put it. “They don’t have
the slightest idea of the ins and outs of Wall Street.”
In buying Carlin they received a crash course. In a stroke Brad
found himself working side by side with a group of American
traders who could not have been less suited to RBC’s culture.
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The first day after the merger, Brad got a call from a worried
female employee, who whispered, “There is a guy in here with
suspenders walking around with a baseball bat in his hands, tak-
ing swings.” That turned out to be Carlin’s founder and CEO,
Jeremy Frommer, who, whatever else he was, was not RBC
nice. One of Frommer ’s signature poses was feet up on his desk,
baseball bat swinging wildly over his head while some poor
shoeshine guy tried to polish his shoes. Another was to find a
perch on the trading floor and muse in loud tones about who
might get fired next. Returning to his alma mater, the Uni-
versity of Albany, to tell a group of business students the secret
of his success, Frommer actually said, “It’s not just enough that
I’m flying in first class. I have to know my friends are flying in
coach.” “Jeremy was emotional, erratic, and loud — everything
the Canadians were not,” says one former senior RBC execu-
tive. “To me, Toronto is like a foreign country,” said Frommer
later. “The people there are not the same culture as us. They
take a very cerebral approach to Wall Street. It was just such a
different world. It was a hard adjustment for me. If you were a
hitter, you couldn’t swing your dick around the way you could
in the old days.”
With each mighty swing Jeremy Frommer scored a direct hit
on Canadian sensibilities. The first Christmas after the two firms
merged, he took it upon himself to organize the office party. The
RBC Christmas party had always been a staid affair. Frommer
rented out Marquee, the Manhattan nightclub. “RBC doesn’t
do stuff at Marquee, says one former RBC trader. “Everyone
was like, ‘What the fuck is going on here?’ ” “I walked in and
I didn’t know ninety percent of the people there,” says another.
“It looked like we were in a Vegas hotel lobby bar. There were
these girls walking around half-naked, selling cigars. I asked,
BRAD’S PROBLEM
29
‘Who are all these people?’” Into this old-fashioned Canadian
bank, heretofore immune from the usual Wall Street patholo-
gies, Frommer imported a bunch of people who were not. “The
women at Carlin had a different look than the women at RBC,”
says another former RBC trader delicately. “You got the feeling
they were hired because they were hot.” With Carlin also came
a boiler room full of day traders, some of whom had rap sheets
with various financial police, others of whom were about to
wind up in jail for financial crimes.” “Carlin was what I always
imagined a bucket shop was like,” says another former RBC
trader. “There was a lot of the gold chains attire,” said another.
It was as if a tribe of 1980s Wall Street alpha males had stum-
bled upon a time machine and, as a prank, identified the most
mild-mannered, well-behaved province in Canada and tele-
ported themselves into it. The RBC guys were at their desks at
6:30; the Carlin guys rolled in at 8:30 or so, looking distinctly
unwell. The RBC guys were understated and polite; the Carlin
guys were brash and loud. “They lied or exaggerated a lot about
their relationships with accounts,” says a current RBC salesman.
“They were like, ‘Yeah, I cover [hedge fund giant John] Paulson
and we’re tight.’ And you’d call Paulson up and they’d barely
heard of the guy.”
For reasons Brad did not fully grasp, RBC insisted that he
move with his entire U.S. stock trading department from their
offices near the World Trade Center site into Carlin’s building in
Midtown. This bothered him a lot. Fie got the distinct impres-
sion that people in Canada had decided that electronic trading
was the future, even if they didn’t understand why or even what
* In the room was, among other people, Zvi Goffer, who was later sentenced to ten years
in jail for orchestrating an insider trading ring in his prior job, with the Galleon Group.
30
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it meant. Installed in Carlin’s offices, the lkBC people were soon
gathered to hear a state-of-the-financial-markets address given
by Frommer. He stood in front of a flat panel computer monitor
that hung on his wall. “He gets up and says the markets are now
all about speed,” says Brad. ‘“Trading is all about speed.’ And
then he says, ‘I’m going to show you how fast our system is.’ He
had this guy next to him with a computer keyboard. He said
to him, ‘Enter an order!’ And the guy hit Enter. And the order
appeared on the screen so everyone could see it. And Frommer
goes, ‘See! See how fast that was!!!’ ” All the guy had done was
type the name ol a stock on a keyboard, and the name was dis-
played on the screen, the way a letter, once it has been typed,
appears on a computer screen. “Then he goes, ‘Do it again!’
And the guy hits the Enter button on the keyboard again. And
everyone nods. It was five in the afternoon. The market wasn’t
open; nothing was happening. But he was like, ‘Oh my God, it’s
happening in real time!’ And I was like, ‘I don’t fucking believe
this. ’ Brad thought: The guy who just sold us our new electronic trad-
ing platform either does not know that his display of technical virtuosity
is absurd, or, worse, he thinks we don’t know.
As it happened, at almost exactly the moment Jeremy From-
mer fully entered Brad’s life, the U.S. stock market began to
behave oddly. Before RBC acquired this supposedly state-of-
the-art electronic trading firm, his computers worked. Now,
suddenly, they didn’t. Until he was forced to use some of Carlin’s
technology, he trusted his trading screens. When his trading
screens showed 10,000 shares of Intel offered at $22 a share, it
meant that he could buy 10,000 shares of Intel for $22 a share.
He had only to push a button. By the spring of 2007, when
his screens showed 10,000 shares of Intel offered at $22 and he
pushed the button, the offers vanished. In his seven years as a
BRAD'S PROBLEM
31
trader he had always been able to look at the screens on his desk
and see the stock market. Now the market as it appeared on his
screens was an illusion.
This was a big problem. Brad’s main role as a trader was to sit
between investors who wanted to buy and sell big amounts of
stock and the public markets, where the volumes were smaller.
Some investor might want to sell a 3-million-share block of
IBM; the markets would only show demand for 1 million shares;
Brad would buy the entire block, sell off a million shares of it
instantly, and then work artfully over the next few hours to
unload the other 2 million shares. If he didn’t know what the
markets actually were, he couldn’t price the larger block. He
had been supplying liquidity to the market; now, whatever was
happening on his screens was reducing his willingness to do it.
Unable to judge market risks, he was less happy to take them.
By June 2007 the problem had grown too big to ignore. An
electronics company in Singapore called Flextronics announced
its intention to buy a smaller rival, Solectron, for a bit less than
$4 a share. A big investor called Brad and said he wanted to sell
5 million shares of Solectron. The public stock markets — the
New York Stock Exchange (NYSE) and Nasdaq — showed the
current market. Say it was 3.70—3.75, which is to say you could
sell Solectron for $3.70 a share or buy it for $3.75. The problem
was that, at those prices, only a million shares were bid for and
offered. The big investor who wished to sell 5 million shares of
Solectron called Brad because he wanted Brad to take the risk
on the other 4 million shares. And so Brad bought the shares at
$3.65, slightly below the price quoted in the public markets. But
when he turned to the public markets — the markets on his trad-
ing screens — the share price instantly moved. Almost as if the
market had read his mind. Instead of selling a million shares at
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FLASH BOYS
$3.70, as he’d assumed he could do, he sold a few hundred thou-
sand and trigged a minicollapse in the price of Solectron. It was
as if someone knew what he was trying to do and was reacting
to his desire to sell before he had fully expressed it. By the time
he was done selling all 5 million shares, at prices far below $3.70,
he had lost a small fortune.
This made no sense to him. He understood how he might
move the price of an infrequently traded stock simply by sat-
isfying the demand for the highest bidder. But in the case of
Solectron, the stock of a company about to be taken over at a
known price by another company was trading heavily. There
should be plenty of supply and demand in a very narrow price
range; it just shouldn’t move very much. The buyers in the mar-
ket shouldn’t vanish the moment he sought to sell. At that point
he did what most people do when they don’t understand why
their computer isn’t working the way it’s supposed to: He called
tech support. “If your keyboard didn’t work, these were the guys
who would come up and replace it.” Like tech support every-
where, their first assumption was that Brad didn’t know what
he was doing. “‘User error’ was the thing they’d throw at you.
They just thought of us traders as a bunch of dumb jocks.” He
explained to them that all he was doing was hitting the Enter
key on his keyboard: It was hard to screw that up.
Once it was clear that the problem was more complicated
than user error, the troubleshooting was bumped to a higher
level. “They started to send me product people, the people
who had bought and installed the systems, and they at least sort
of sounded like technologists.” He explained that the market
on his screens used to be a fair representation of the actual
stock market but that now it was not. In return he received
mainly blank stares. It wound up being me talking to some-
BRAD’S PROBLEM
33
one and them looking, like, befuddled.” Finally he complained
so loudly that they sent him the developers, the guys who had
come to RBC in the Carlin acquisition. “We would hear how
they had this roomful of Indians and Chinese guys. Rarely
would you see them on the trading floor. They were called “the
Golden Goose.” The bank did not want the Golden Goose dis-
tracted, and, when the geese arrived, they had the air of people
on leave from some critical mission. They, too, explained to
Brad that he, and not his machine, was the problem. “They
told me it was because I was in New York and the markets
were in New Jersey and my market data was slow. Then they
said that it was all caused by the fact that there are thousands
of people trading in the market. They’d say, ‘You aren’t the
only one trying to do what you’re trying to do. There’s other
events. There’s news.’ ”
If that was the case, he asked them, why did the market in
any given stock dry up only when he was trying to trade in it?
To make his point, he asked the developers to stand behind
him and watch while he traded. “I’d say, ‘Watch closely. I
am about to buy one hundred thousand shares of Amgen. I
am willing to pay forty-eight dollars a share. There are cur-
rently one hundred thousand shares of Amgen being offered at
forty-eight dollars a share — ten thousand on BATS, thirty-five
thousand on the New York Stock Exchange, thirty thousand
on Nasdaq, and twenty-five thousand on Direct Edge.’ You
could see it all on the screens. We’d all sit there and stare at the
screen and I’d have my finger over the Enter button. I’d count
out loud to five . . .
“ ‘One . . .
“ ‘Two. . . . See, nothing’s happened.
“ ‘Three. . . . Offers are still there at forty-eight . . .
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“ ‘Four. . . . Still no movement.
“‘Five.’ Then Fd hit the Enter button and — boom! — all hell
would break loose. The offerings would all disappear, and the
stock would pop higher.”
At which point he turned to the guys standing behind him
and said, “You see, Fm the event. I am the news.”
To that the developers had no response. “They were kind of
like, ‘Ohhh, yeah. Let me look into that.’ Then they’d disap-
pear and never come back.” Fie called a few times, but “when I
realized they really had no shot at solving the problem, I just left
them alone.”
Brad suspected that the culprit was the technology from Car-
lin that RBC had more or less bolted onto the side of his trad-
ing machines. “As the market problem got worse,” he said, “I
started to just assume my real problem was with how bad their
technology was.” A pattern was established: The moment he
attempted to react to the market on his screens, the market
moved. And it wasn’t just him: The exact same thing was hap-
pening to all of the RBC stock market traders who worked for
him. In addition, for reasons he couldn’t fathom, the fees that
RBC was paying to stock exchanges were suddenly skyrocket-
ing. At the end of 2007 Brad conducted a study to compare
what had happened on his trading books to what should have
happened, or what used to happen, when the stock market as
stated on his trading screens was the market he experienced.
“The difference to us was tens of millions of dollars” in losses
plus fees, he said. “We were hemorrhaging money.” His bosses
in Toronto called him in and told him to figure out how to
reduce his rising trading costs.
Up till then, Brad had taken the stock exchanges for granted.
When he’d arrived in New York, in 2002, 85 percent of all stock
BRAD’S PROBLEM
35
market trading happened on the New York Stock Exchange,
and some human being processed every order. The stocks that
didn’t trade on the New York Stock Exchange traded on Nas-
daq. No stocks traded on both exchanges. At the behest of the
SEC, in turn responding to public protests about cronyism, the
exchanges themselves, in 2005, went from being utilities owned
by their members to public corporations run for profit. Once
competition was introduced, the exchanges multiplied. By early
2008 there were thirteen different public exchanges, most of
them in northern New Jersey. Virtually every stock now traded
on all of these exchanges: You could still buy and sell IBM on
the New York Stock Exchange, but you could also buy and
sell it on BATS, Direct Edge, Nasdaq, Nasdaq BX, and so on.
The idea that a human being needed to stand between investors
and the market was dead. The “exchange” at Nasdaq or at the
New York Stock Exchange, or at their new competitors, such
as BATS and Direct Edge, was a stack of computer servers that
contained the program called the “matching engine.” There was
no one inside the exchange to talk to. You submitted an order
to the exchange by typing it into a computer and sending it into
the exchange’s matching engine. At the big Wall Street banks,
the guys who once peddled stocks to big investors had been
reprogrammed. They now sold algorithms, or encoded trading
rules designed by the banks, that investors used to submit their
stock market orders. The departments that created these trading
algorithms were dubbed “electronic trading.”
That was why the Royal Bank of Canada had panicked and
bought Carlin. There was still a role for Brad and traders like
Brad — to sit between buyers and sellers of giant blocks of stock
and the market. But the space was shrinking.
At the same time, the exchanges were changing the way they
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made money. In 2002 they charged every Wall Street broker who
submitted a stock market order the same simple fixed commis-
sion per share traded. Replacing people with machines enabled
the markets to become not just faster but more complicated. The
exchanges rolled out an incredibly complicated system of fees
and kickbacks. The system was called the “maker-taker model”
and, like a lot of Wall Street creations, was understood by almost
no one. Even professional investors’ eyes glazed over when Brad
tried to explain it to them. It was the one thing I'd skip, because
a lot of people just didn’t get it,” he said. Say you wanted to buy
shares in Apple, and the market in Apple was 400-400.05. If you
simply went in and bought the shares at $400.05, you were said
to be “crossing the spread.” The trader who crossed the spread
was classified as the taker. If you instead rested your order to
buy Apple at $400, and someone came along and sold the shares
to you at $400, you were designated a “maker.” In general, the
exchanges charged takers a few pennies a share, paid makers
somewhat less, and pocketed the difference — on the dubious
theory that whoever resisted the urge to cross the spread was
performing some kind of service. But there were exceptions.
For instance, the BATS exchange, in Weehawken, New Jersey,
perversely paid takers and charged makers.
In early 2008 all of this came as news to Brad Katsuyama. “I
thought all the exchanges just charged us a flat fee,” he said. “I’m
like, ‘Holy shit, you mean someone will pay us to trade?’ ” Think-
ing he was being clever, he had all of RBC’s trading algorithms
direct the bank s stock market orders to whatever exchange
would pay them the most for what they wanted to do — which,
at that moment, happened to be the BATS exchange. “It was a
total disaster, said Brad. When he tried to buy or sell stock and
seize the payment from the BATS exchange, the market for that
BRAD’S PROBLEM
37
stock simply vanished, and the price of the stock moved away
from him. Instead of being paid, he wound up hemorrhaging
even more money.
It was not obvious to Brad why some exchanges paid you to
be a taker and charged you to be a maker, while others charged
you to be a taker and paid you to be a maker. No one he asked
could explain it, either. “It wasn’t like there was anyone saying,
‘Hey, you should really be paying attention to this.’ Because no
one was paying attention to this.” To further bewilder the Wall
Street brokers who sent stock market orders to the exchanges, the
amounts that were charged varied from exchange to exchange,
and the exchanges often changed their pricing. To Brad this
all just seemed bizarre and unnecessarily complicated — and it
raised all sorts of questions. “Why would you pay anyone to be
a taker? I mean, who is willing to pay to make a market? Why
would anyone do that?”
He took to asking people around the bank who might know
more than he did. He tried Googling, but there wasn’t really
anything to Google. One day he was talking to a guy who
worked on the retail end in Toronto selling stocks to individual
Canadians. “I said, ‘I’m getting screwed, but I can’t figure out
who is screwing me.’ And he says, ‘You know, there are more
players out there in the market now.’ And I say, ‘What do you
mean more players ?’ He says, ‘You know, there’s this new firm
that’s now ten percent of the U.S. market.’ ” The guy mentioned
the firm’s name, but Brad didn’t fully catch it. It sounded like
Gekko. (The name was Getco.) “I’d never even heard of Getco.
I didn’t even know the name. I’m like, ‘WHAT??’ They were
ten percent of the market. How can that be true? It’s insane
that someone could be ten percent of the U.S. stock market and
I’m running a Wall Street trading desk and I’ve never heard of
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the place. And why, he wondered, would a guy from retail in
Canada know about them first?
He was now running a stock market trading department
unable to trade properly in the U.S. stock market. He was forced
to watch people he cared for harassed and upset by a bunch of
1980s Wall Street throwbacks. And then, in the fall of 2008, as
he sat and wondered what else might go wrong, the entire U.S.
financial system went into a freefall. The way Americans han-
dled their money had led to market chaos, and the market chaos
created life chaos: The jobs and careers of everyone around him
were suddenly on the line. “Every day I’d walk home and feel as
it I had just got hit by a car.”
He wasn’t naive. He knew that there were good guys and bad
guys, and that sometimes the bad guys win; but he also believed
that usually they did not. That view was now challenged. When
he began to grasp, along with the rest of the world, what big
American firms had done— rigged credit ratings to make bad
loans seem like good loans, created subprime bonds designed to
fail, sold them to their customers and then bet against them, and
so on his mind hit some kind of wall. For the first time in his
career, he felt that he could only win if someone else lost, or,
more likely, that someone else could only win if he lost. He was
not by nature a zero-sum person, but he had somehow wound
up in the middle of a zero-sum business.
His body had always tended to register stress before his mind.
It was as if his mind refused to accept the possibility of conflict
even as his body was engaged in that conflict. Now he bounced
from one illness to another. His sinuses became infected and
required surgery. His blood pressure, chronically high, skyrock-
eted. His doctors had him seeing a kidney specialist.
By early 2009 he’d decided to quit Wall Street. He’d just
BRAD’S PROBLEM
39
become engaged. After work every day he’d sit down with his
fiancee, Ashley Hooper — a recent Ole Miss graduate who’d
grown up in Jacksonville, Florida — to decide where to live.
They’d whittled the list down to San Diego, Atlanta, Toronto,
Orlando, and San Francisco. He had no idea what he was going
to do; he just wanted out. “I thought I could just sell pharmaceu-
ticals or whatever.” He’d never felt a need to be on Wall Street.
“It was never a calling,” he said. “1 didn’t think about money
or the stock market when I was growing up. So the attach-
ment was not strong.” Maybe more oddly, he hadn’t become
all that wedded to money, even though RBC was now paying
him almost $2 million a year. His heart had been in his job, but
mainly because he really liked the people he worked for and the
people who worked for him. What he liked about RBC was
that it had never pressured him to be anyone but himself. The
bank — or the markets, or perhaps both — was now pushing him
to be someone else.
Then the bank, on its own, changed its mind. In February
2009 RBC parted ways with Jeremy Frommer and asked Brad
to help find someone to replace him. Even as he had one foot
out the door, Brad found himself interviewing candidates from
all over Wall Street — and he saw that basically none of the peo-
ple who held themselves out as knowledgeable about electronic
trading understood it. “The problem was that the electronic
people facing clients were just front men,” he said. “They had
no clue how the technology worked.”
He withdrew his foot from the doorway and thought about it.
Every day, the markets were driven less directly by human beings
and more directly by machines. The machines were overseen
by people, of course, but few of them knew how the machines
worked. He knew that RBC’s machines — not the computers
40
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themselves, but the instructions to run them — were third-rate,
but he had assumed it was because the company’s new electronic
trading unit was bumbling and inept. As he interviewed people
from the major banks on Wall Street, he came to realize that
they had more in common with RBC than he had supposed.
“I’d always been a trader,” he said. “And as a trader you’re kind
of inside a bubble. You’re just watching your screens all day.
Now I stepped back and for the first time started to watch other
traders.” He had a good friend who traded stocks at a big-time
hedge fund in Greenwich, Connecticut, called SAC Capital.
SAC Capital was famous (and soon to be infamous) for being
one step ahead of the U.S. stock market. If anyone was going
to know something about the market that Brad didn’t know,
he figured, it would be them. One spring morning he took the
train up to Greenwich and spent the day watching his friend
trade. Right away he saw that, even though his friend was using
technology given to him by Goldman Sachs and Morgan Stan-
ley and the other big firms, he was experiencing exactly the
same problem as RBC: The market on his screens was no longer
the market. His friend would hit a button to buy or sell a stock
and the market would move away from him. “When I see this
guy trading and he was getting screwed — I now see that it isn’t
just me. My frustration is the market’s frustration. And I was
like, Whoa, this is serious.”
Brad’s problem wasn’t just Brad’s problem. What people saw
when they looked at the U.S. stock market — the numbers on the
screens of the professional traders, the ticker tape running across
the bottom of the CNBC screen — was an illusion. “That’s when
I realized the markets are rigged. And I knew it had to do with
the technology. That the answer lay beneath the surface of the
technology. I had absolutely no idea where. But that’s when the
BRAD’S PROBLEM
41
lightbulb went off that the only way I’m going to find out what’s
going on is if I go beneath the surface.”
THERE WAS NO way he, Brad Katsuyama, was going to go below
the surface of the technology. People always assumed, because
he was an Asian male, that he must be a computer wizard. He
couldn’t (or wouldn’t) program his own VCR. What he had was
an ability to distinguish between computer people who didn’t
actually know what they were talking about and those who did.
The very best example of the latter, he thought, was Rob Park.
Park, a fellow Canadian, was a legend at RBC. In college in
the late 1990s he’d become entranced by what was then a novel
idea: to teach a machine to behave like a very smart trader. “The
thing that interested me was taking a trader’s thought process
and replicating it,” Park said. He and Brad had worked together
at RBC only briefly, back in 2004, before he left to start his
own business, but they had hit it off. Rob took an interest in
the way Brad thought when he traded. Rob then turned those
thoughts into code. The result was RBC’s most popular trad-
ing algorithm. Here’s how it worked: Say the trader wanted to
buy 100,000 shares in General Motors. The algo scanned the
market; it saw that there were only 100 shares offered. No smart
trader seeking to buy 100,000 shares would tip his desire for a
mere 100 shares. The market was too thin. But what was the
point at which the trader should buy GM stock? The algo-
rithm Rob built had a trigger point: It only bought stock if the
amount on offer was greater than the historical average of the
amount offered. That is, if the market was thick. “The decisions
he makes make sense,” Brad said of Rob. “He puts an incred-
ible amount of thought into them. And since he puts so much
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thought into his decisions, he’s capable of explaining those deci-
sions to others.”
After Brad persuaded Rob to return to RBC, he had the per-
fect person to figure out what had happened to the U.S. stock
market. And in Brad, Rob saw the perfect person to grasp and
explain to others whatever he discovered. “All Brad needs is a
translator from computer language to human language,” said
Park. “Once he has a translator, he completely understands it.”
Brad wasn’t exactly shocked when RBC finally gave up look-
ing for someone to run its mess of an electronic trading opera-
tion and asked him if he would take it over and fix it. Everyone
else was shocked when he agreed to do it, as (a) he had a safe
and cushy $2-million-a-year job running the human traders
and (b) RBC had nothing to add to electronic trading. The mar-
ket was cluttered; big investors had only so much space on their
desks for trading algorithms sold by brokers; and Goldman Sachs
and Morgan Stanley and Credit Suisse had long since overrun
that space and colonized it. All that was left of RBC’s purchase
of Carlin was the Golden Goose. Thus Brad’s first question to
the Golden Goose: How do we plan to make money? They had
an answer: They planned to open RBC’s first “dark pool.” That,
as it turned out, was what the Golden Goose had been up to all
along, writing the software for the dark pool.
Dark pools were another rogue spawn of the new financial
marketplace. Private stock exchanges, run by the big brokers,
they were not required to reveal to the public what happened
inside them. They reported any trade they executed, but they did
so with sufficient delay that it was impossible to know exactly
what was happening in the broader market at the moment the
trade occurred. Their internal rules were a mystery, and only
the broker who ran a dark pool knew for sure whose buy and sell
BRAD’S PROBLEM
43
orders were allowed inside. The amazing idea the big Wall Street
banks had sold to big investors was that transparency was their
enemy. If, say, Fidelity wanted to sell a million shares of Microsoft
Corp. — so the argument ran — they were better off putting them
into a dark pool run by, say, Credit Suisse than going directly to
the public exchanges. On the public exchanges, everyone would
notice a big seller had entered the market, and the market price
of Microsoft would plunge. Inside a dark pool, no one but the
broker who ran it had any idea what was happening.
The cost of RBC’s creating and running its own dark pool,
Brad now learned, would be nearly $4 million a year. Thus
his second question for the Golden Goose: How will we make
more than $4 million from our own dark pool? The Golden
Goose explained that they’d save all sorts of money in fees
they paid to the public exchanges — by putting together buy-
ers and sellers of the same stocks who came to RBC at the
same time. If RBC had some investor who wanted to buy a
million shares of Microsoft, and another who wanted to sell
a million shares of Microsoft, they could simply pair them off
in the dark pool rather than pay Nasdaq or the New York Stock
Exchange to do it. In theory this made sense; in practice, not so
much. “The problem,” said Brad, “was RBC was two percent
of the market. I asked how often we were likely to have buyers
and sellers to cross. No one had done the analysis.” The analy-
sis, once finished, showed that RBC, if it opened a dark pool
and routed all its clients’ orders into it first, would save about
$200,000 a year in exchange fees. “So I said, ‘Okay, how else
will we make money?’ ”
The answer that came back explained why no one had both-
ered to do any analysis on dark pools in the first place. There
was a lot of free money to be made, the computer programmers
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explained, by selling access to the RBC dark pool to outside
traders. They said there were all these people who will pay to
be in our dark pool,” recalled Brad. “And I said, ‘Who would
pay to be in our dark pool? And they said, ‘High-frequency
traders. Brad tried to think of good reasons why traders of
any sort would pay RBC for access to RBC’s customers’ stock
market orders, but he came up with none. “It just felt weird,”
he said. “I had a feeling of why and the feeling didn’t feel good.
So I said, ‘Okay, none of this sounds like a good idea. Kill the
dark pool.’ ”
That just pissed off a lot of people and fueled suspicions that
Brad Katsuyama was engaged in some activity other than the
search for corporate profits. Now he was in charge of a business
called electronic trading — with nothing to sell. What he had,
instead, was a fast-growing pile of unanswered questions. Why,
between the dark pools and the public exchanges, were there
nearly sixty different places, most of them in New Jersey, where
you could buy any listed stock? Why did the public exchanges
fiddle with their own pricing so often — and why did you get paid
by one exchange to do exactly the same thing for which another
exchange might charge you? How did a firm he’d never heard
°f — Getco — trade 10 percent of the entire volume of the stock
market? How had this guy in the middle of nowhere — in retail in
Canada — learned of Getco’s existence before him? Why was the
market displayed on Wall Street trading screens an illusion?
In May 2009, what appeared to be a scandal involving the
public stock exchanges added more questions to Brad’s list.
New York senator Charles Schumer wrote a letter to the
SEC — then issued a press release telling the world what he had
done — condemning the stock exchanges for allowing “sophisti-
cated high-frequency traders to gain access to trading mforma-
BRAD’S PROBLEM
45
tion before it is sent out widely to other traders. For a fee, the
exchange will ‘flash’ information about buy and sell orders for
just a few fractions of a second before the information is made
publicly available.” That was the first time that Brad had heard
the term “flash orders.” To the growing list of mental questions,
he added another: Why would stock exchanges have allowed
flash trading in the first place?
HE AND ROB set out to build a team of people to investigate the
U.S. stock market. “At first 1 was looking for guys who had
worked in HFT or who had worked at large banks,” said Brad.
No one who had worked in high-frequency trading would
return his calls. Finding people who worked for the big banks
was easier: Wall Street firms were shedding people. Guys who
wouldn’t have given RBC a second thought were now turning
up in his office begging for work. “I interviewed more than
seventy-five people,” he said. “We didn’t hire any of them.” The
problem with all of these people was that even when they said
they had worked in electronic trading, they clearly didn’t under-
stand how the electronics did the trading.
Instead of waiting for resumes to find him, Brad went looking
for people who worked in or near the banks’ technology depart-
ments. In the end his new team consisted of a former Deutsche
Bank software programmer named Billy Zhao, a former man-
ager in Bank of America’s electronic trading division named John
Schwall, and a twenty-two-year-old recent Stanford computer
science graduate named Dan Aisen. Fie then set out with Rob
for Princeton, New Jersey, where the Golden Goose resided, to
figure out if any pieces of the Goose were worth keeping. There
they found a Chinese programmer named Allen Zhang, who,
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FLASH BOYS
it turned out, had written the computer code for the doomed
dark pool. “I couldn’t tell who was good and who was not from
just talking to them, but Rob could,” said Brad. “And it became
clear that Allen was the Goose.” Or, at any rate, the only part
of the Goose that might be turned to gold. Allen, Brad noticed,
had no interest in conforming to the norms of corporate life. He
preferred to work on his own, in the middle of the night, and
refused to ever take off his baseball cap, which he wore pulled
down low over his eyes, giving him the appearance of a getaway
driver badly in need of sleep. Allen was also incomprehensible:
What was just possibly English came tumbling out of him so
quickly and indistinctly that his words tended to freeze the lis-
tener in his tracks. As Brad put it, “Whenever Allen said any-
thing, I’d turn to Rob and say, ‘What the fuck did he just say?’ ”
Once he had a team in place, Brad persuaded his superiors
at the Royal Bank of Canada to conduct what amounted to a
series of science experiments in the U.S. stock markets. For the
next several months he and his team would trade stocks not to
make money but to test theories — to try to answer his original
question: Why was there a difference between the stock market
displayed on his trading screens and the actual market? Why,
when he went to buy 20,000 shares of IBM offered on his trad-
ing screens, did the market only sell him 2,000? To search for
an answer, RBC agreed to let his team lose up to $10,000 a day.
Brad asked Rob to come up with some theories to spend the
money on.
The obvious place to start was the public markets — the thir-
teen stock exchanges scattered in four different sites run by the
New York Stock Exchange, Nasdaq, BATS, and Direct Edge.
Rob invited the exchanges to send representatives to RBC to
answer a few questions. “We were asking really basic questions:
BRAD’S PROBLEM
47
‘How does your matching engine work?’ ” recalls Park. “ ‘How
does it handle a lot of different orders at the same price?’ But
they sent salespeople and they had no idea. When we kept push-
ing, they sent product managers, business people who knew a
little about the technology — but they really didn’t know much.
They finally sent developers.” They were the guys who actually
programmed the machines. “The question we wanted to answer
was, ‘What happens between the time you push the button to
trade and the time your order gets to the exchange?’ ” says Park.
“People think pushing a button is as simple as pushing a button.
It’s not. All these things have to happen. There’s a ton of stuff'
happening. The data we got from them about what was happen-
ing at first just seemed random. But we knew the answer was out
there. It was just a question of how to find it.”
Rob’s first theory was that the exchanges weren’t simply bun-
dling all the orders at a given price but arranging them in some
kind of sequence. You and I might both submit an order to
buy 1,000 shares of IBM at $30 a share, but you might some-
how obtain the right to cancel your order if my order is filled.
“We started getting the idea that people were canceling orders,”
says Park. “That they were just phantom orders.” Say the mar-
kets, together, showed 10,000 shares of Apple offered at $400 a
share. Typically, that didn’t represent one person who wanted
to sell 10,000 shares of Apple but rather a bunch of smaller sell
orders lumped together. They suspected that the orders were
lined up in such a way that some people at the back of the line
had the ability to jump out of the queue the moment the peo-
ple in the front of the line sold their shares. “We tried calling
the exchanges and asking them if that’s what they did,” said
Park. “But we didn’t even know what words to use.” The fur-
ther problem was that the trading reports did not separate out
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FLASH BOYS
the exchanges: If you tried to buy 10,000 shares of Apple that
seemed to be on offer and succeeded in buying only 2,000 of
them, you weren’t informed which exchanges the 8,000 missing
shares had vanished from.
Allen wrote a new program that allowed Brad to send orders
to a single exchange. Brad was fairly certain that this would
prove that some, or maybe even all, of the exchanges were
allowing these phantom orders. But no: When he sent an order
to a single exchange, he was able to buy everything on offer.
The market as it appeared on his screens was, once again, the
market. “I thought, Crap, there goes that theory,” said Brad.
“And that’s our only theory.”
It made no sense: Why would the market on the screens be
real if you sent your order only to one exchange but prove illu-
sory when you sent your order to all the exchanges at once?
Lacking an actual theory, Brad’s team began to send orders into
various combinations of exchanges. First NYSE and Nasdaq.
Then NYSE and Nasdaq and BATS. Then NYSE, Nasdaq BX,
Nasdaq, and BATS. And so on. What came back was a further
mystery. As they increased the number of exchanges, the per-
centage of the order that was filled decreased; the more places
they tried to buy stock from, the less stock they actually bought.
“There was one exception,” said Brad. “No matter how many
exchanges we sent an order to, we always got one hundred per-
cent of what was offered on BATS.” Rob Park studied this and
said, “I had no idea why this would be. I just thought, BATS is
a great exchange!”
One morning, while taking a shower, Rob had another the-
ory. He was picturing a bar chart Allen had created. It showed
the time it took orders to travel from Brad’s trading desk in the
World Financial Center to the various exchanges. (To wide-
BRAD'S PROBLEM
49
spread relief, they’d left Carlin’s old offices and moved back
downtown.) “I was just visualizing that chart,” he said. “It just
occurred to me that the bars are different heights. What if they
were the same height? That got me fired up immediately. I went
to work and went right to Brad’s office and said, ‘I think it’s
because we’re not arriving at the same time.’ ”
The increments of time involved were absurdly small: In
theory, the shortest travel time, from Brad’s desk to the BATS
exchange in Weehawken, was about 2 milliseconds, and the
slowest, from Brad’s desk to Carteret, was around 4 millisec-
onds. In practice, the times could vary much more than that,
depending on network traffic, static, and glitches in the pieces
of equipment between any two points. It took 100 milliseconds
to blink your eyes; it was hard to believe that a fraction of the
blink of an eye could have such vast market consequences. Allen
wrote a program — this one took him a couple of days — that
built delays into the orders Brad sent to exchanges that were
faster to get to, so that they arrived at exactly the same time
as they did at the exchanges that were slower to get to. “It was
counterintuitive,” says Park. “Because everyone was telling us it
was all about faster. We had to go faster. And we were slowing
it down.” One morning they sat down at the screen to test the
program. Ordinarily, when you hit the button to buy and failed
to get the stock, the screens lit up red; when you got only some
of the stock you were after, the screens lit up brown; and when
you got everything you asked for, the screens lit up green. Allen
hadn’t taken his Series 7 exam, which meant he wasn’t allowed
to press the Enter button and make a trade, so Rob actually hit
the button. Allen watched the screens light up green, and, as
he later said, “I had the thought: This is too easy.” Rob did not
agree. “As soon as I pushed the button, I ran to Brad’s desk,”
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recalled Rob. “ ‘It worked! It fucking worked.’ I remember there
was a pause and then Brad said, ‘Now what do we do?’ ”
That question implied an understanding: Someone out there
was using the fact that stock market orders arrived at differ-
ent times at different exchanges to front-run orders from one
market to another. Knowing that, what do you do next? That
question suggested another: Do you use this knowledge to join
whatever game is being played in the stock market? Or for some
other purpose? It took Brad roughly six seconds to answer the
question. “Brad said, ‘We have to go on an educational cam-
paign,’ ” recalls Park. “It would have been very easy to make
money off this. He just chose not to.”
THEY NOW HAD an answer to one of their questions — which, as
always, raised another question. “It’s 2009,” said Brad. “This had
been happening to me for almost three years. There’s no way
I’m the first guy to have figured this out. So what happened to
everyone else?” They also had a tool they could sell to investors:
the program Allen had written to build delays into the stock
exchange orders. Before they did that, they wanted to test it on
RBC’s own traders. “I remember being at my desk,” said Park,
“and you hear people going, ‘OOOOOOO!’ and ‘Holy shit,
you can buy stock!’ ” The tool enabled the traders to do the job
they were meant to do: take risk on behalf of the big investors
who wanted to trade big chunks of stock. They could once again
trust the market on their screens. The tool needed a name. Brad
and his team stewed over this until one day a trader stood up at
his desk and hollered, “Dude, you should just call it Thor! The
hammer!” Someone was assigned to figure out what Thor might
be an acronym for, and they found some words that worked, but
BRAD’S PROBLEM
51
no one remembered them. The tool was always just Thor. “I
knew we were onto something when Thor became a verb,” said
Brad. “When I heard guys shouting, ‘Thor it!’”
The other way he knew they were on to something was from
conversations he had with a few of the world’s biggest money
managers. The first visit Brad and Rob Park made was to Mike
Gitlin, who oversaw $700 billion in U.S. stock market invest-
ments for T. Rowe Price. The story they told didn’t come to
Gitlin as a complete shock. “You could see that something had
just changed,” said Gitlin. “You could see that when you were
trading a stock, the market knew what you were going to do,
and it was going to move against you.” But what Brad described
was a far more detailed picture of the market than Gitlin had ever
considered — and, in that market, all the incentives were screwed
up. The Wall Street brokerage firm deciding where to send
T. Rowe Price’s buy and sell orders had a great deal of power
over how and where those orders got submitted. The firms were
now paid for sending orders to some exchanges and billed for
sending orders to others. Did the broker resist these incentives
when they didn’t align with the interests of the investors he was
meant to represent? No one could say. Another wacky incentive
was called “payment for order flow.” As of 2010, every Ameri-
can stockbroker and all the online brokers effectively auctioned
their customers’ stock market orders. The online broker TD
Ameritrade, for example, was paid hundreds of millions of dol-
lars each year to send their orders to a high-frequency trading
firm called Citadel, which executed the orders on their behalf.
Why was Citadel willing to pay so much to see the flow? No
one could say with certainty.
It had been hard to measure the cost of the new market struc-
ture. But now there was a tool for gauging not just how orders
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reached their destination but also how much money this new
Wall Street intermediation machine was removing from the
pockets of investors large and small: Thor. Brad explained to
Mike Gitlin how his team had placed big trades to measure how
much more cheaply they bought stock when they removed the
ability of the machine to front-run them. For instance, they
bought 10 million shares of Citigroup, then trading at roughly
$4 per share, and saved $29,000 — or less than a tenth of 1 per-
cent of the total price. “That was the tax,” said Rob Park. It
sounded small until you realized that the average daily volume
in the U.S. stock market was $225 billion. The same tax rate
applied to that sum came to more than $160 million a day. “It
was so insidious because you couldn’t see it,” said Brad. “It hap-
pens on such a granular level that even if you tried to line it up
and figure it out you wouldn’t be able to do it. People are getting
screwed because they can’t imagine a microsecond.”
Thor showed you what happened when a Wall Street firm
helped an investor to avoid paying the tax. The evidence was
indirect but, to Gitlin’s mind, damning. The mere existence
of Brad Katsuyama was totally shocking. “To have RBC have
the foremost electronic trading expert in the world was a little
strange,” said Gitlin. “You would not think that is where the
world’s foremost electronic expert would reside.”
The discovery of Thor was not the end of a story; it was
closer to a beginning. Brad and his team were building a mental
picture of the financial markets after the crisis. The market was
now a pure abstraction. It called to mind no obvious picture
to replace the old one that people still carried around in their
heads. The same old ticker tape ran across the bottom of televi-
sion screens — even though it represented only a tiny fraction of
the actual trading. Market experts still reported from the floor
BRAD’S PROBLEM
53
of the New York Stock Exchange, even though trading no lon-
ger happened there. For a market expert truly to get inside
the New York Stock Exchange, he’d need to climb inside a
tall black stack of computer servers locked inside a cage locked
inside a fortress guarded by a small army of heavily armed men
and touchy German shepherds in Mahwah, New Jersey. If he
wanted an overview of the entire stock market — or even the
trading in a single company like IBM — he’d need to inspect
the computer printouts from twelve other public exchanges
scattered across northern New Jersey, plus records of the private
dealings that occurred inside the growing number of dark pools.
If he tried to do this, he’d soon learn that there actually was no
computer printout. At least no reliable one. No mental picture
existed of the new financial market. There was only this yellow-
ing photograph of a market now dead that served as a stand-in
for the living.
Brad had no idea how dark and difficult the picture he’d create
would become. All he knew for sure was that the stock market
was no longer a market. It was a collection of small markets scat-
tered across New Jersey and lower Manhattan. When bids and
offers for shares sent to these places arrived at precisely the same
moment, the markets acted as markets should. If they arrived
even a millisecond apart, the market vanished, and all bets were
off. Brad knew that he was being front-run — that some other
trader was, in effect, noticing his demand for stock on one
exchange and buying it on others in anticipation of selling it to
him at a higher price. Ele’d identified a suspect: high-frequency
traders. “I had a sense that the problems are being caused by this
new participant in the market,” said Brad. “I just didn’t know
how they were doing it.”
By late 2009 U.S. high-frequency trading firms were flying
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to Toronto with offers to pay Canadian banks to expose their
customers to high-frequency traders. Earlier that year, one of
RBC’s competitors, the Canadian Imperial Bank of Commerce
(CIBC), had sublet its license on the Toronto Stock Exchange to
several high-frequency trading firms and, within a few months,
had seen its historically stable 6-7 percent share of Canadian
stock market trading triple.* Senior managers at the Royal Bank
of Canada were now arguing that the bank should create a Cana-
dian dark pool, route their Canadian customers’ stock market
orders into it, and then sell to high-frequency traders the right
to operate inside the dark pool. Brad thought that it made a lot
more sense for RBC simply to expose the new game for what it
was, and perhaps establish themselves as the only broker on Wall
Street not conspiring to screw investors. “The only card left to
play was honesty,” as Rob Park put it.
Brad argued to his bosses that he should be permitted to
launch what amounted to a public information campaign. He
wanted to go out and explain, to anyone with money to invest
in the United States stock markets, that they were now the prey.
He wanted to tell them about this new weapon they might use
to defend themselves from the predator. But the market was
* The rules of the Canadian stock market are different from the rules of the U.S. stock
market. One rule in Canada that does not exist in the United States is “broker priority.”
The idea is to enable brokerage firms that have both sides of a trade to pair off buyers and
sellers without the interference of other buyers and sellers. For example, imagine that
CIBC (representing some investor) has a standing order to buy shares in Company X at
$20 a share, but that it is not alone, and several other banks also have standing orders for
Company X’s shares at $20. If CIBC then enters the market with an order from another
CIBC customer to sell shares in Company X at $20, the CIBC buyer has priority on
the trade and is the first to have his order filled. By allowing high-frequency traders to
operate with CIBC’s license, CIBC was, in effect, creating lots of collisions between its
own customers and the HFT firms.
BRAD’S PROBLEM
55
already pressuring him to say nothing at all. He was in a race
to win a debate in front of RBC’s top management about how
to respond to the newly automated stock markets. All he had
going for him was his weird discovery, which proved . . . what,
exactly? That the stock market now behaved strangely, except
when it didn’t? The RBC executives who wanted to join forces
with high-frequency traders knew as little about high-frequency
trading as he did. “I needed someone from the industry to verify
that what I was saying was real,” said Brad. He needed, specifi-
cally, someone from deep inside the world of high-frequency
trading. He’d spent the better part of a year cold-calling strang-
ers in search of an HFT strategist willing to defect. He now sus-
pected that every human being who knew how high-frequency
traders made money was making too much money doing it to
stop and explain what was going on. He needed to find another
way in.
CHAPTER THREE
RONAN’S PROBLEM
P art of Ronan’s problem was that he didn’t look like a Wall
Street trader. He had pale skin and narrow, stooped shoul-
ders, and the uneasy caution of a man who has survived
one potato famine and is expecting another. He also lacked the
Wall Street trader’s ability to bury his self-doubt, and to seem
more important and knowledgeable than he actually was. He
was wiry and wary, like a mongoose. And yet from the moment
he caught his first glimpse of a Wall Street trading floor, in his
early twenties, Ronan Ryan badly wanted to work on Wall
Street — and couldn’t understand why he didn’t belong. “It’s hard
not to get enamored of being one of these Wall Street guys who
people are scared of and make all this money,” he said. But it was
hard to imagine anyone being scared of Ronan.
The other part of Ronan’s problem was his inability or
unwillingness to disguise his modest origins. Born and raised in
Dublin, he’d moved to America in 1990, when he was sixteen.
The Irish government had sent his father to New York to talk
RONAN’S PROBLEM
57
American companies into moving to Ireland for the tax benefits,
but few imagined that they would do so. Ireland was poor and
dreary (“kind of like a shithole, to be honest”). His father, who
was not made of money, had spent every last penny he had to
rent a house in Greenwich, Connecticut, so that Ronan might
attend the Greenwich public high school and see what life was
like on the “right side of the tracks.” “I couldn’t believe it,” says
Ronan. “The kids had their own cars at sixteen! Kids would
complain they had to ride on a school bus. I’d say, ‘This fucking
thing actually takes you to school! And it’s free! I used to walk
three miles.’ It’s hard not to love America.” When Ronan was
twenty-two, his father was recalled to Ireland; Ronan stayed
behind. He didn’t think of Ireland as a place anyone would
ever go back to if given the choice, and he’d now embraced his
idea of the American Dream — Greenwich, Connecticut, ver-
sion. The year before, through an Irish guy his father had met,
he’d landed a summer internship in the back office at Chemical
Bank and had been promised a place in the management train-
ing program.
Then they canceled the training program; the Irish guy van-
ished. Graduating from Fairfield University in 1996, he sent let-
ters to all the Wall Street banks but received just one false flicker
of interest, from what, even to his untrained eyes, was a vaguely
criminal, pump-and-dump penny stock brokerage firm. “It’s
not as easy as you think to get a job on Wall Street,” he said. “I
didn’t know anyone. My family had no contacts whatsoever. We
knew no one.”
Eventually he gave up trying. He met another Irish guy who
happened to work in the New York office of MCI Communi-
cations, the big telecom company. “He gave me a job strictly
because I was Irish,” said Ronan. “I guess he had a few charity
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cases a year. I was one of them.” For no particular reason other
than that no one else would hire him, he went to work in the
telecom industry.
The first big job they gave him was to make sure that the
eight thousand new pagers MCI had sold to a big Wall Street
firm were well received. As he was told, “People are really sensi-
tive about their pagers.” Ronan traveled in the back of a repair
truck in the summer heat to some office building to deliver the
new pagers. He set up his little table at the back of the truck and
unpacked the crates and waited for the Wall Street people to
come and get their new pagers. An hour into it he was sweat-
ing and huffing inside the truck while a line of people waited
for their pagers, and a crowd had formed, of guys to whom he’d
already given the pagers: pager protestors. “These new pagers
suckl ” and “I hate this fucking pager!” they screamed, as he tried
to pass out even more pagers. As he dealt with the revolt, one
of the Wall Street firms’ secretaries called him about her boss’s
new pager. She was so despondent about the thing that Ronan
thought he could hear her crying. “She keeps saying over and
over, ‘It’s too big! It’s going to really hurt him! It’s too big! It’s
going to really hurt him!’ ” Ronan was now totally confused:
How could a pager inflict harm on a grown man? It was a tiny
box, an inch by an inch and a half. “Then she tells me he’s a
midget, and it would dig into his side when he bent over,” said
Ronan. “And that he wasn’t like a normal-sized midget. He was
a really small dude. And I’m thinking, but I don’t say it because I
don’t want her to think I’m a dick, Why don’t you just strap it onto
his back, like a backpack?”
At that moment, and others like it, many things crossed
Ronan s mind that he did not say. Sizing pagers to little Wall
Street people, and being hollered at by big Wall Street people
RONAN’S PROBLEM
59
who didn’t like their new gadgets, was not what he’d imagined
doing with his life. He was upset he hadn’t found a path onto
Wall Street. He decided to make the best of it.
That turned out to be the view that MCI offered him of the
entire U.S. telecom system. Ronan had always been handy, but
he’d never actually studied anything practical. He knew next to
nothing about technology. Now he started to learn all about it.
“It’s pretty captivating, when you take the nerdiness out of it,
how this shit works,” he said. How a copper circuit conveyed
information, compared to a glass fiber. How a switch made by
Cisco compared to a switch made by Juniper. Which hardware
companies made the fastest computer equipment, and which
buildings in which cities contained floors that could withstand
the weight of that equipment — old manufacturing buildings
were best. He also learned how information actually traveled
from one place to another — which was usually not in a straight
line run by a single telecom carrier but in a convoluted path run
by several. “When you make a call to New York from Florida,
you have no idea how many pieces of equipment you have to
go through for that call to happen. You probably just think it’s
fucking like two cans and a piece of string. But it’s not.” A cir-
cuit that connected New York City to Florida would have Veri-
zon on the New York end, BellSouth on the Florida end, and
MCI in the middle; it would zigzag from population center to
population center; once it got there it would wind in all sorts
of crazy ways through skyscrapers and city streets. To sound
knowing, telecom people liked to say that the fiber routes ran
through “the NFL cities.”
That was another thing Ronan learned: A lot of people in
and around the telecom industry were more knowing than
knowledgeable. The people at MCI who sold the technology
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often didn’t actually understand it and yet were paid far better
than people, like him, who simply fixed problems. Or, as he put
it, “I’m making thirty-five and they’re making a buck twenty
and they’re fucking idiots.” He got himself moved to sales and
became a leading salesperson. A few years into the job, he was
lured from MCI by Qwest Communications; three years later,
he was lured from Qwest by another big telecom carrier, Level 3.
He was now making good money — a couple of hundred grand a
year. By 2005, he also couldn’t help but notice, his clients were
more likely than ever to be big Wall Street banks. He spent
entire weeks inside Goldman Sachs and Lehman Brothers and
Deutsche Bank, figuring out the best routes to run fiber and the
best machines to hook that fiber up to. He hadn’t lost his origi-
nal ambition. At some point on every Wall Street job he had,
he’d nose around for a job opening. “I’m thinking: I’m meeting
so many people. Why can’t I get a job at one of these places?”
Actually, the big banks offered him jobs all the time, but the jobs
were never finance jobs. They offered him tech jobs — working
in some remote site with computer hardware and fiber-optic
cable. There was a vividly clear class distinction between tech
guys and finance guys. The finance guys saw the tech guys as
faceless help and were unable to think of them as anything else.
“They always said the same thing to me: ‘You’re a boxes and
lines guy,’ ” he said.
Then, in 2006, BT Radianz called. Radianz was born of
9/11, after the attacks on the World Trade Center knocked out
big pieces of Wall Street’s communication system. The company
promised to build for big Wall Street banks a system less vulner-
able to outside attack than the existing system. Ronan’s job was
to sell the financial world on the idea of subcontracting their
information networks to Radianz. In particular, he was meant
RONAN’S PROBLEM
61
to sell the banks on “co-locating” their computers in Radianz’s
data center in Nutley, New Jersey. But not long after he started
his job at Radianz, Ronan had a different sort of inquiry, from
a hedge fund based in Kansas City. The caller said he worked
at a stock market trading firm called Bountiful Trust, and that
he had heard Ronan was expert at moving financial data from
one place to another. Bountiful Trust had a problem: In making
trades between Kansas City and New York, it took them too
long to determine what happened to their orders — that is, what
stocks they had bought and sold. They also noticed that, increas-
ingly, when they placed their orders, the market was vanishing
on them, just as it was vanishing on Brad Katsuyama. “He says,
‘My latency time is forty-three milliseconds,’ ” recalls Ronan.
“And I said, ‘What the hell is a millisecond?’ ”
Latency was simply the time between the moment a signal
was sent and when it was received. There were several factors
that determined the latency of a stock market trading system: the
boxes, the logic, and the lines. The boxes were the machinery
the signals passed through on their way from Point A to Point
B: the computer servers and signal amplifiers and switches. The
logic was the software, the code instructions that operated the
boxes. Ronan didn’t know much about software, except that,
more and more, it seemed to be written by Russian guys who
barely spoke English. The lines were the glass fiber-optic cables
that carried the information from one box to another. The sin-
gle biggest determinant of speed was the length of the fiber, or
the distance the signal needed to travel to get from Point A to
Point B. Ronan didn’t know what a millisecond was, but he
understood the problem with this Kansas City hedge fund: It
was in Kansas City. Light in a vacuum traveled at 186,000 miles
per second, or, put another way, 186 miles a millisecond. Light
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inside of fiber bounced oft' the walls and so traveled at only about
two-thirds of its theoretical speed. But it was still fast. The big-
gest enemy of the speed of a signal was the distance the signal
needed to travel. “Physics is physics — this is what the traders
didn’t understand,” said Ronan.
The whole reason Bountiful Trust had set up shop in Kansas
City was that its founders believed that it no longer mattered
where they were physically located. That Wall Street was no
longer a place. They were wrong. Wall Street was, once again, a
place. It wasn’t actually on Wall Street now. It was in New Jer-
sey. Ronan moved the computers from Kansas City to Radianz’s
data center in Nutley and reduced the time it took them to find
out what they had bought and sold from 43 milliseconds to 3.8
milliseconds.
From that moment the demand on Wall Street for Ronan’s
services intensified. Not just from banks and well-known high-
frequency trading firms but also from prop shops (proprietary
trading firms) no one had ever heard of, with just a few guys in
them. All wanted to be able to trade faster than the others. To
be faster they needed to find shorter routes for their signals to
travel; to be faster they needed the newest hardware, stripped
down to its essentials; to be faster they also needed to reduce the
physical distance between their computers and the computers
inside the various stock exchanges. Ronan knew how to solve
all of these problems. But as all his new customers housed their
computers inside the Radianz data center in Nutley, this was a
tricky business. Ronan says, “One day a trader calls and asks,
Where am I in the room?’ I’m thinking, In the room? What do
you mean ‘in the room’? What the guy meant, it turned out, was in
the room." He was willing to pay to move his computer that sent
orders into the stock market as close as possible to the pipe that
RONAN’S PROBLEM
63
exited the building in Nutley — so that he would have a slight
jump on the other computers in the room. Another trader then
called Ronan to say that he had noticed that his fiber-optic cable
was a few yards longer than it needed to be. Instead of having
it wind around the outside of the room with everyone else’s
cable — which helped to reduce the heat in the room — the trader
wanted his cable to hew a straight line right across the middle
of the room.
It was only a matter of time before the stock exchanges figured
out that, if people were willing to spend hundreds of thousands
of dollars to move their machines around inside some remote
data center just so they might be a tiny bit closer to the stock
exchange, they’d pay millions to be inside the stock exchange
itself. Ronan followed them there. He came up with an idea:
sell proximity to Wall Street as a service. Call it “proximity ser-
vices.” “We tried to trademark proximity, but you can’t because
it’s a word,” he said. What he wanted to call proximity soon
became known as “co-location,” and Ronan became the world’s
authority on the subject. When they ran out of ways to reduce
the length of their cable, they began to focus on the devices on
either end of the cable. Data switches, for instance. The differ-
ence between fast data switches and slow ones was measured in
microseconds (millionths of a second), but microseconds were
now critical. “One guy says to me, ‘It doesn’t matter if I’m one
second slower or one microsecond; either way I come in sec-
ond place.’” The switching times fell from 150 microseconds
to 1.2 microseconds per trade. “And then,” says Ronan, “they
started to ask, ‘What kind of glass are you using?’ ” All opti-
cal fibers were not created equal; some kinds of glass conveyed
light signals more efficiently than others. And Ronan thought:
Never before in human history have people gone to so much
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trouble and spent so much money to gain so little speed. “People
were measuring the length of their cables to the foot inside the
exchanges. People were buying these servers and chucking them
out six months later. For microseconds.”
He didn’t know how much money high-frequency traders
were making, but he could guess from how much they were
spending. From the end of 2005 to the end of 2008, Radi-
anz alone billed them nearly $80 million — -just for setting up
their computers near the stock exchange matching engines. And
Radianz was hardly the only one billing them. Seeing that the
fiber routes between the New Jersey exchanges were often less
than ideal, Ronan prodded a company called Hudson Fiber into
finding straighter ones. Hudson Fiber was now doing a land-
office business digging trenches in places that would give Tony
Soprano pause. Ronan could also guess how much money high-
frequency traders were making by the trouble they took to con-
ceal how they made it. One HFT firm he set up inside one of the
stock exchanges insisted that he wrap their new computer serv-
ers in wire gauze — to prevent anyone from seeing their blink-
ing lights or improvements in their hardware. Another HFT
firm secured the computer cage nearest the exchange’s matching
engine — the computer code that, in effect, was now the stock
market. Formerly owned by Toys “R” Us (the computers prob-
ably ran the toy store’s website), the cage was emblazoned with
store logos. The HFT firm insisted on leaving the Toys “R” Us
logos in place so that no one would know they had improved
their position, in relation to the matching engine, by several
feet. “They were all paranoid,” said Ronan. “But they were
right to be. If you know how to pickpocket someone and you
were the pickpocketer, you would do the same thing. You’d see
someone find a new switch that was three microseconds faster,
RONAN’S PROBLEM
65
and in two weeks everyone in the data center would have the
same switch.”
By the end of 2007 Ronan was making hundreds of thousands
of dollars a year building systems to make stock market trades
faster. He was struck, over and over again, by how little the
traders he helped understood of the technology they were using.
“They’d say, ‘Aha! I saw it — -it’s so fast!’ And I’d say, ‘Look, I’m
happy you like our product. But there’s no fucking way you saw
anything.’ And they’re like, ‘I saw it!’ And I’m like, ‘It’s three
milliseconds — it’s fifty times faster than the blink of an eye.’ ”
He was also keenly aware that he had only the faintest idea of
the reason for this incredible new lust for speed. He heard a
lot of loose talk about “arbitrage,” but what, exactly, was being
arbitraged, and why did it need to be done so fast? “I felt like the
getaway driver,” he said. “Each time, it was like, ‘Drive faster!
Drive faster!’ Then it was like, ‘Get rid of the airbags!’ Then it
was, ‘Get rid of the fucking seats!’ Towards the end I’m like,
‘Excuse me, sirs, but what are you doing in the bank?’ ” He had
a sense of the technological aptitude of the various players. The
two biggest high-frequency trading firms, Citadel and Getco,
were easily the smartest. Some of the prop shops were smart,
too. The big banks, at least for now, were all slow.
Beyond that, he didn’t even really know much about his cli-
ents. The big banks — Goldman Sachs, Credit Suisse — everyone
had heard of. Others — Citadel, Getco — were famous on a small
scale. He learned that some of these firms were hedge funds,
which meant that they took money from outside investors. But
most of them were prop shops, trading only their own found-
ers’ money. A huge number of the firms he dealt with — Hudson
River Trading, Eagle Seven, Simplex Investments, Evolution
Financial Technologies, Cooperfund, DRW — no one had ever
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heard of, and the firms obviously intended to keep it that way.
The prop shops were especially strange, because they were
both transient and prosperous. “They’d be just five guys in a
room. All of them geeks. The leader of each five-man pack is
just an arrogant version of that geek. A fucking arrogant ver-
sion of that.” One day a prop shop was trading; the next, it had
closed, and all the people in it had moved to work for some big
Wall Street bank. One group of guys Ronan saw over and over:
four Russian, one Chinese. The arrogant Russian guy who was
clearly their leader was named Vladimir. Vladimir and his boys
ping-ponged from prop shop to big bank and back to prop shop,
writing the computer code that made the actual stock market
trading decisions. Ronan watched them meet with one of the
most senior guys at a big Wall Street bank that hoped to employ
them — and the Wall Street big shot sucked up to them. “He
walks into the meeting and says, ‘I’m always the most important
man in the room, but in this case Vladimir is.’ ’ Ronan knew
that these roving bands of geeks felt nothing but condescen-
sion toward the less technical guys who ran the big Wall Street
firms. I was listening to them talk about some calculation they
had been asked to make, and Vladimir goes, ‘Ho, ho, ho. That’s
what Americans call math.’ He said it like moth. That’s what
Americans call moth. I thought, I’m fucking Irish, but fuck you
guys. This country gave you a shot.”
By early 2008 Ronan was spending a lot of his time abroad,
helping high-frequency traders exploit the Americanization of
foreign stock markets. A pattern emerged: A country in which
the stock market had always traded on a single exchange —
Canada, Australia, the UK — would, in the name of free-market
competition, permit the creation of a new exchange. The new
exchange was always located at some surprising distance from the
RONAN’S PROBLEM
67
original exchange. In Toronto it was inside an old department
store building across the city from the Toronto Stock Exchange.
In Australia it was mysteriously located not in the Sydney finan-
cial district but across Sydney Harbor, in the middle of a resi-
dential district. The old London Stock Exchange was in central
London. BATS created a British rival in the Docklands, NYSE
created another, outside of London, in Basildon, and Chi-X cre-
ated a third in Slough. Each new exchange gave rise to the need
for high-speed routes between the exchanges. “It was almost
like they picked places to set up exchanges so that the market
would fragment,” said Ronan.
He still didn’t have a job on Wall Street, but Ronan had every
reason to be pleased with himself and with his career. In 2007,
the first year of the speed boom, he’d made $486,000, nearly
twice as much as he’d ever made. Yet he did not feel pleased
with himself or with his career. He was obviously good at what
he did, but he had no idea why he was doing it, and he wanted
to. At the end of 2007, on New Year’s Eve, he found himself
sitting in a pub in Liverpool with “Let It Be” playing dully on
the radio. His wife had given him the trip as this lovely gift.
Around a miniature soccer ball she’d wrapped a note that said
she’d bought him a plane ticket to England and a ticket to see his
favorite football team. “I’m doing something I always dreamed
about doing, and it was about the most depressing moment I’ve
ever had in my life,” said Ronan. “I’m thirty-four years old. I’m
thinking it’s never going to get any better. I’m going to be fuck-
ing Willy Loman for the rest of my life.” He felt ordinary.
In the fall of 2009, out of the blue, the Royal Bank of Canada
called him and invited him to interview for a job. He was more
than a little wary. He’d barely heard of RBC, and when he
checked out their website it told him next to nothing. He’d
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grown weary of self-important Wall Street traders who wanted
him to do their manual labor for them. “I said, ‘I mean no
disrespect, but if you’re calling to offer me some tech job, I
have no fucking interest.’ ” The RBC guy who called him —
Brad Katsuyama — insisted that it wasn’t a tech job but a job in
finance, on a trading floor.
Ronan met Brad at seven the next morning and wondered if
that was a Wall Street thing, hauling people in for interviews at
seven in the morning. Brad asked him a bunch of questions and
then invited him back to meet his bosses. In what seemed to
Ronan like “the quickest hiring in the history of Wall Street,”
RBC offered him a job on the trading floor. It paid $125,000,
or roughly a third of what Ronan was making peddling speed
to high-frequency traders. It came with a fancy title: Head of
High-Frequency Trading Strategies. For a chance to work on a
Wall Street trading floor, Ronan was willing to take a big pay
cut. “To be honest, I would have taken less,” he said. But the
title disturbed him, because, as he put it, “I didn’t know any
high-frequency trading strategies.” He was so excited to have
finally landed a job on a Wall Street trading floor that he didn’t
bother to ask the obvious question. His wife asked it for him.
“She says to me, ‘What are you going to do for them?’ And I
realized I didn’t really fucking know. I really, honest to God,
have no idea what the job is. There was no job description ever
discussed. He never told me what he wanted me for.”
IN THE FALL of 2009, an article in a trade magazine caught Brad
Katsuyama’s eye. He’d spent the better part of a year trying and
failing to find anyone who actually worked in what was now
regularly referred to as high-frequency trading who was willing
RONAN’S PROBLEM
69
to explain to him how he made his money. The article claimed
that HFT technologists were unhappy with the widening gulf
in pay between themselves and the senior trading strategists of
their firms, some of whom were rumored to be taking home
hundreds of millions of dollars a year. He went looking for one
of these unhappy technologists. The very first call he made, to a
guy at Deutsche Bank who dealt often with HFT, gave him two
names. Ronan’s was the first.
In his interview, Ronan described to Brad what he’d wit-
nessed inside the exchanges: the frantic competition for nano-
seconds, the Toys “R” Us cage, the wire gauze, the war for space
within the exchanges, the tens of millions being spent by high-
frequency traders for tiny increments of speed. As he spoke, he
filled huge empty tracts on Brad’s mental map of the financial
markets. “What he said told me that we needed to care about
microseconds and nanoseconds,” said Brad. The U.S. stock mar-
ket was now a class system, rooted in speed, of haves and have-
nots. The haves paid for nanoseconds; the have-nots had no idea
that a nanosecond had value. The haves enjoyed a perfect view
of the market; the have-nots never saw the market at all. What had
once been the world’s most public, most democratic, financial
market had become, in spirit, something more like a private
viewing of a stolen work of art. “I learned more from talking to
him in an hour than I learned from six months of reading about
HFT,” said Brad. “The second I met him I wanted to hire him.”
He wanted to hire him without being able to fully explain, to
his bosses or even to Ronan, what he wanted to hire him for. He
couldn’t very well call him Vice President in Charge of Explain-
ing to My Clueless Superiors Why High-Frequency Trading Is
a Travesty. So he called him Head of High-Frequency Trading
Strategies. “I felt he needed a ‘Head of’ title,” said Brad, “to get
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more respect from people.” That was Brad’s main concern: that
people on the trading floor, even at RBC, would take one look
at Ronan and see a guy in a yellow jumpsuit who’d just emerged
from some manhole. Ronan didn’t even pretend to know what
happened on a trading floor. “He had questions that were unbe-
lievably rudimentary but that were necessary,” said Brad. “He
didn’t know what ‘bid’ and ‘offer’ was. He didn’t know what it
meant to ‘cross the spread.’ ”
On the side, without making a big deal of it, Brad started to
teach Ronan the language of trading. A “bid” was an attempt
to buy stock, an “offer” an attempt to sell it. To cross the spread,
if you were selling, meant to accept the bidder’s price, or, if you
were buying, the ottering price. “This fucking guy didn’t laugh
at me,” said Ronan. “He sat down and explained it.” That was
their private deal: Brad would teach Ronan about trading, and
Ronan would teach Brad about technology.
Right away there was something to teach. Brad and his team
were having trouble turning Thor into a product they could
sell to investors. The investors they’d told about their discov-
ery were clearly eager to buy Thor and use it for themselves —
T. Rowe Price’s Gitlin had more or less tried to buy it on the
spot — but Thor now had its problems. The experiment of arriv-
ing at the exchanges at the same time had worked perfectly — the
first time. It proved hard to repeat, because it was difficult to
coax thirteen light signals to arrive in thirteen different stock
exchanges spread across northern New Jersey within 350 micro-
seconds of each other — or roughly 100 microseconds less than
the time they had calculated it would take some high-speed
trader to front-run their order. They’d succeeded the first time
by estimating the differences in travel time it took to send the
messages to the various exchanges, and by building the equiva-
RONAN’S PROBLEM
71
lent delays into their software. But the travel times were never
the same. They had no control over the path the signals took to
get to the exchanges, or how much traffic was on the network.
Sometimes it took 4 milliseconds for their stock market orders
to arrive at the New York Stock Exchange; other times, it took
7 milliseconds. When the travel time differed from their guesses
of what it would be, the market, once again, vanished.
In short, Thor was inconsistent; and it was inconsistent, Ronan
explained, because the paths the electronic signals took from
Brad’s desk to the various exchanges were inconsistent. Ronan
could see that these traders hadn’t thought much about the phys-
ical process by which their signals traveled to the New Jersey
stock exchanges. “I realized very quickly,” he said, “and they’ll
admit this, so I mean no disrespect, that they had no fucking
clue what they were doing.” The signal sent from Brad’s desk
arrived at the New Jersey exchanges at different times because
some exchanges were farther from Brad’s desk than others. The
fastest any high-speed trader’s signal could travel from the first
exchange it reached to the next one was 465 microseconds, or
one two-hundredths of the time it takes to blink your eye, if you
have a talent for it. That is, for Brad’s trading orders to interact
with the market as displayed on his trading screens, they needed
to arrive at all the exchanges within a 465 -microsecond win-
dow. The only way to do that, Ronan told his new colleagues at
RBC, was to build and control your own fiber network.
To make his point, Ronan brought in oversized maps of
New Jersey showing the fiber-optic networks built by telecom
companies. On the maps you could see just how a signal trav-
eled from Brad’s trading station at One Liberty Plaza to the
exchanges. When he unrolled his first map, a guy who worked
in RBC’s network support team burst out, “How the fuck did
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you get those? They’re telecom property! They’re proprietary!”
Ronan explained, “When they said they wouldn’t give them to
me because they were proprietary, I said, Well, then, propri-
etarily fuck off.’ ” The high-frequency traders were paying the
telecom carriers too much to be denied whatever they wanted,
and Ronan had been the agent of their desires. “These maps are
like fucking gold,” he said. “But I had brought them so much
business that they would let me see inside their freaking wife’s
underwear drawer if I asked them to.”
The maps told a story: Any trading signal that originated in
lower Manhattan traveled up the West Side Highway and out
the Lincoln Tunnel. Perched immediately outside the tunnel, in
Weehawken, New Jersey, was the BATS exchange. From BATS
the routes became more complicated, as they had to find their
way through the clutter of the Jersey suburbs. “New Jersey is
now carved up like a Thanksgiving turkey,” said Ronan. One
way or another, they traveled east to Secaucus, the location of
the Direct Edge family of exchanges founded by Goldman Sachs
and Citadel, and south to the Nasdaq family of exchanges in
Carteret. The New York Stock Exchange further complicated
the story. In early 2010, NYSE still had its computer servers in
lower Manhattan, at 55 Water Street. (They moved them to
distant Mahwah, New Jersey, that August.) As it was less than a
mile from Brad’s desk, NYSE appeared to be the stock market
closest to him; but Ronan’s maps showed the incredible indirec-
tion of optic fiber in Manhattan. “To get from Liberty Plaza
to Fifty-five Water Street, you might go through Brooklyn,”
he explained. “You can go fifty miles to get from Midtown to
downtown. To get from a building to a building across the street
you could travel fifteen miles.” It was a ten-minute walk from
RBC’s office at Liberty Plaza to the New York Stock Exchange.
RONAN’S PROBLEM
73
But from a computer’s point of view, the New York Stock
Exchange was further from RBC’s offices than Carteret.
To Brad the maps explained, among other things, why the
market on BATS had proved so accurate. The reason they were
always able to buy or sell 100 percent of the shares listed on
BATS was that BATS was always the first stock market to receive
their orders. News of their buying and selling hadn’t had time
to spread throughout the marketplace. “I was like, ‘Holy shit,
BATS is just closest to us.’ It’s right outside the freaking tunnel.”
Inside BATS, high-frequency trading firms were waiting for
news that they could use to trade on the other exchanges. They
obtained that news by placing very small bids and offers, typi-
cally for 100 shares, for every listed stock. Having gleaned that
there was a buyer or seller of Company X’s shares, they would
race ahead to the other exchanges and buy or sell accordingly.
(The race they needed to win was not a race against the ordi-
nary investor, who had no clue what was happening to him, but
against other high-speed traders.) The orders resting on BATS
were typically just the 100-share minimum required for an
order to be at the front of any price queue, as their only purpose
was to tease information out of investors. The HFT firms posted
these tiny orders on BATS — orders to buy or sell 100 shares of
basically every stock traded in the U.S. market — not because
they actually wanted to buy and sell the stocks but because they
wanted to find out what investors wanted to buy and sell before
they did it. BATS, unsurprisingly, had been created by high-
frequency traders.
The funny thing was that a lot of what Ronan had seen and
heard didn’t make sense to him: He didn’t know what he knew.
Brad now helped him to understand. For instance, Ronan had
noticed the HFT guys creating elaborate tables of the time,
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measured in microseconds, it took for a stock market order to
travel from any given brokerage house to each of the exchanges.
Latency tables,” these were called. The times were subtly differ-
ent for every brokerage house — they depended upon where the
brokerage house physically was located and which fiber networks
it leased in New Jersey. These tables took trouble to create and
were of obvious value to high-frequency traders, but Ronan had
no idea why. This was the first Brad had heard of latency tables,
but he knew exactly why they had been created: They enabled
high-frequency traders to identify brokers by the time their
orders took to travel from one exchange to the other. Once you
had figured out which broker was behind any given stock mar-
ket order, you could discern patterns in each broker’s behavior.
If you knew which broker had just come into the market with
an order to buy 1,000 shares of IBM, you might further guess
whether those 1,000 shares were the entire order or a part of a
much larger order. You might also guess how the broker might
distribute the order among the various exchanges and how much
above the current market price for IBM shares the broker might
be willing to pay. The HFT guys didn’t need perfect informa-
tion to make riskless profits; they only needed to skew the odds
systematically in their favor. But, as Brad put it, “What you’re
looking for ultimately is large brokers who are behaving idioti-
cally with their customers’ orders. That’s the real gold mine.”
He also knew that Wall Street brokers had a new incentive
to behave idiotically, because he had himself succumbed to the
temptation. When Wall Street decided where to route their cli-
ents’ stock market orders, they were now greatly influenced by
the new system of kickbacks paid and fees charged to them by the
exchanges: If a big Wall Street broker stood to be paid to send an
order to buy 10,000 shares of IBM to BATS but was charged to
RONAN’S PROBLEM
75
send the same order to the New York Stock Exchange, it would
program its routers to send the customer’s order to BATS. The
router, designed by human beings, took on a life of its own.
Along with the trading algorithms, the routers were a criti-
cal piece of technology in the automated stock markets. Both
are designed and built by people who work for the Wall Street
broker. Both do the thinking that people used to do, but the
intellectual tasks they perform are different. The algorithm does
its thinking first: It decides how to slice up any given order.
Say you want to buy 100,000 shares of XYZ Company at no
more than $25 a share, when the market shows a total of 2,000
shares offered at $25. To simply attempt to buy 100,000 shares
all at once would create havoc in the market and drive the price
higher. The algorithm decides how many shares you buy, when
to buy them, and the price to pay. For example, it may instruct
the router to carve the 100,000-share order into twenty pieces,
and to buy 5,000 shares every five minutes, so long as the price
is no higher than $25.
The router determines where the order is sent. For instance, a
router might instruct the order to go first to a Wall Street firm’s
dark pool before going to the exchanges. Or it might instruct the
order to go first to any exchange that will pay the broker to trade,
and only then to exchanges on which the broker will be compelled
to pay to trade. (This is a so-called sequential cost-effective router.)
To illustrate how stupid routing can be, say you have told your
Wall Street broker — to whom you are paying a commission — that
you wish to buy 100,000 shares of Company XYZ at $25 and
now, conveniently, there are 100,000 shares for sale at $25, 10,000
on each of ten different exchanges, all of which will charge the
broker to trade on your behalf (though far less than the com-
mission you have paid to him). There are, however, another 100
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shares for sale, also at $25, on the BATS exchange — which will
pay the broker for the trade. The sequential cost-effective router
will go first to BATS and buy the 100 shares — and cause the other
100,000 shares to vanish into the paws of high-frequency trad-
ers (in the bargain relieving the broker of the obligation to pay
to trade). The high-frequency traders can then turn around and
sell the shares of Company XYZ at a higher price, or hold onto
the shares for a few seconds more, while you, the investor, chase
Company XYZ’s shares even higher. In either case, the result is
unappealing to the original buyer of Company XYZ’s shares.
That is but the most obvious of many examples of routing stu-
pidity. The customer (you, or someone investing on your behalf)
is typically entirely oblivious to the inner workings of both algo-
rithms and routers: Even if he demanded to know how his order
was routed, and his broker told him, he would never be sure what
was said was true, as he has no sufficiently detailed record of what
shares traded and when they traded.
The brokers’ routers, like bad poker players, all had a con-
spicuous tell. The tell might be a glitch in their machines rather
than a twitch of their facial muscles, but it was just as valuable to
the HFT guys on the other side of the table.
Once Brad had explained all of this to Ronan, he didn’t need
to explain it again. “It was, ‘Oh shit, some of the things I over-
heard now make more sense,’ ” said Ronan.
With Ronan’s help, the RBC team designed their own fiber
network and turned Thor into a product that could be sold to
investors. The sales pitch was absurdly simple: There is a new
predator in the financial markets. Here is how he operates, and we have
a weapon you can use to defend yourself against him. The argument
about whether RBC should leap into bed with high-frequency
traders ended. Brad’s new problem was spreading the word of
RONAN’S PROBLEM
77
what he now knew to the U.S. investing public. Seeing how
shocked people were by what Ronan had to say, and how inter-
ested they were in it, and no longer needing Ronan to per-
suade his bosses that something strange and new was afoot, Brad
decided to set Ronan loose on Wall Street’s biggest customers.
“Brad calls me in and says, ‘What if we stop calling you Head of
High-Frequency Trading Strategy and make you Head of Elec-
tronic Trading Strategy?,’ ” said Ronan, who had no idea what
either title actually meant. “I called my wife and said, ‘I think
they just promoted me.’ ”
A few days later, Ronan went with Brad to his first Wall
Street meeting. “Right before the meeting, Brad says, ‘What
are you going to say? What have you prepared?’ I hadn’t pre-
pared anything, so I said, ‘I’ll just wing it.’ ” He now had a
pretty good idea why Brad had given him a new job title. “My
role was to walk around and say to clients, ‘Don’t you under-
stand you’re being fucked?’ ” The man on the other end of this
first extemporaneous presentation — the president of a $9 billion
hedge fund — recalls the encounter this way: “I know I have a
three-hundred-million-dollar problem on a nine-billion-dollar
hedge fund.” (That is, he knows that the cost of not being
able to trade at the stated market prices is costing him $300
million a year.) “But I don’t know exactly what the problem
is. As he’s talking, I’m saying to myself, RBC doesn’t even
know what they are doing. And who are these guys? They
aren’t traders. They’re not salesguys. And they’re not quants.
So what are they? And then they say they have a solution to the
world’s problems. And you’re like: ‘What? How on earth can
I even trust you?’ And then they totally explain my problem.”
Between them, Brad and Ronan told this hedge fund manager
all they had learned. They explained, in short, how the infer-
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mational value of everything this man did with money was
being auctioned by brokers and exchanges to high-frequency
trading firms so that they might exploit him. That was why he
had a $300 million problem on a $9 billion fund.
After Brad and Ronan had left his office, the president of
this big hedge fund, who had never before thought of himself
as prey, reconsidered the financial markets. He sat at his desk
watching both his personal online brokerage account and his
$l,800-a-month Bloomberg terminal. In his private brokerage
account he set out to buy an exchange-traded fund (ETF) com-
prised of Chinese construction companies. Over several hours
he watched the price of the fund on his Bloomberg terminal.
It was midnight in China, nothing was happening, and the
ETF’s price didn’t budge. He then clicked the Buy button on his
online brokerage account screen, and the price on the Bloom-
berg screen jumped. Most people who used online brokerage
accounts didn’t have Bloomberg terminals that enabled them
to monitor the market in something close to real time. Most
investors never would know what happened in the market after
they pressed the Buy button. “I hadn’t even hit Execute,” says
the hedge fund president. “I hadn’t done anything but put in a
ticker symbol and a quantity to buy. And the market popped.”
Then, after he had bought his ETF at a higher price than origi-
nally listed, the hedge fund president received a confirmation
saying that the trade had been executed by Citadel Derivatives.
Citadel was one of the biggest high-frequency trading firms.
“And I wondered, Why is my online broker sending my trades
to Citadel?”
Brad had observed and encouraged a lot of Wall Street careers,
but, as he said, “I’d never seen anyone’s star rise as quickly as
Ronan’s did. He just took off.” Ronan, for his part, couldn’t
RONAN’S PROBLEM
79
quite believe how ordinary the people on Wall Street were. “It’s
a whole industry of bullshit,” he said. The first thing that struck
Ronan about a lot of the big investors he met was their inse-
curity. “People in this industry don’t want to admit they don’t
know something,” he said. “Almost never do they say, ‘No, I
don’t know. Tell me.’ I’d say, ‘Do you know what co-location
is?’ And they’d say, ‘Oh yeah, I know about co-location.’ Then
I’d say, ‘You know, HFT now puts their servers in the same
building with the exchange, as close as possible to the exchange’s
matching engine, so they get market data before everyone else.’
And people are like, ‘What the fuck??!! That’s got to be illegal!’
We met with hundreds of people. And no one knew about it.”
He was also surprised to find how wedded they were to the big
Wall Street banks, even when those banks failed them. “In HFT
there was no loyalty whatsoever,” he said. Over and over again,
investors would tell Ronan and Brad how outraged they were
that the big Wall Street firms that handled their stock market
orders had failed to protect them from this new predator. Yet
they were willing to give RBC only a small percentage of their
trades to execute. “This was the biggest confusion to me about
Wall Street,” said Ronan. “ ‘Wait, you’re telling me you can’t
pay us because you need to pay all these other people who are
trying to screw you?’ ”
Maybe because Ronan was so unlike a Wall Street person, he
was granted special access and was able to get inside the heads of
the Wall Street people to whom he spoke. “After that first meet-
ing, I told him there was no point in us even being in the same
meeting,” said Brad. “We needed to divide and conquer.”
By the end of 2010, Brad and Ronan between them met with
roughly five hundred professional stock market investors who
controlled, among them, many trillions of dollars in assets. They
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never created a PowerPoint; they never did anything more for-
mal than sit down and tell people everything they knew in plain
English. Brad soon realized that the most sophisticated investors
didn’t know what was going on in their own market. Not the
big mutual funds, Fidelity and Vanguard. Not the big money
management firms like T. Rowe Price and Janus Capital. Not
even the most sophisticated hedge funds. The legendary inves-
tor David Einhorn, for instance, was shocked; so was Dan Loeb,
another prominent hedge fund manager. Bill Ackman ran a
famous hedge fund, Pershing Square, that often made bids for
large chunks of companies. In the two years before Brad turned
up in his office to explain what was happening, Ackman had
started to suspect that people might be using the information
about his trades to trade ahead of him. “I felt that there was a
leak every time,” says Ackman. “I thought maybe it was the
prime broker. It wasn’t the kind of leak that I thought.” A sales-
man Brad hired at RBC from Merrill Lynch to help him mar-
ket Thor recalls one big investor calling to say, “You know,
I thought I knew what I did for a living but apparently not,
because I had no idea this was going on.”
Then came the so-called flash crash. At 2:45 on May 6, 2010,
for no obvious reason, the market fell six hundred points in a
few minutes. A few minutes later, like a drunk trying to pre-
tend he hadn’t just knocked over the fishbowl and killed the
pet goldfish, it bounced right back up to where it was before. If
you weren’t watching closely you could have missed the entire
event — unless, of course, you had placed orders in the mar-
ket to buy or sell certain stocks. Shares of Procter & Gamble,
for instance, traded as low as a penny and as high as $100,000.
Twenty thousand different trades happened at stock prices more
than 60 percent removed from the prices of those stocks just
RONAN’S PROBLEM
81
moments before. Five months later, the SEC published a report
blaming the entire fiasco on a single large sell order, of stock
market futures contracts, mistakenly placed on an exchange in
Chicago by an obscure Kansas City mutual fund.
That explanation could only be true by accident, because the
stock market regulators did not possess the information they
needed to understand the stock markets. The unit of trading
was now the microsecond, but the records kept by the exchanges
were by the second. There were one million microseconds in
a second. It was as if, back in the 1920s, the only stock market
data available was a crude aggregation of all trades made during
the decade. You could see that at some point in that era there
had been a stock market crash. You could see nothing about the
events on and around October 29, 1929. The first thing Brad
noticed as he read the SEC report on the flash crash was its old-
fashioned sense of time. “I did a search of the report for the word
‘minute,’ ” said Brad. “I got eighty-seven hits. I then searched for
‘second’ and got sixty-three hits. I then searched for ‘millisec-
ond’ and got four hits- — none of them actually relevant. Finally,
I searched for ‘microsecond’ and got zero hits.” He read the
report once and then never looked at it again. “Once you get a
sense of the speed with which things are happening, you realize
that explanations like this — someone hitting a button — are not
right,” he said. “You want to see a single time-stamped sheet of
every trade. To see what followed from what. Not only does it
not exist, it can’t exist, as currently configured.”
No one could say for sure what caused the flash crash — for
the same reason no one could prove that high-frequency traders
were front-running the orders of ordinary investors. The data
didn’t exist. But Brad sensed that the investment community
was not persuaded by the SEC’s explanation and by the assur-
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ances of the stock exchanges that all was well inside them. A
lot of them asked the same question he was asking himself: Isn’t
there a much deeper question of how this one snowball caused
a deadly avalanche? He watched the most sophisticated inves-
tors respond after Duncan Niederauer, the CEO of the New
York Stock Exchange, embarked on a goodwill tour, the pur-
pose of which seemed to be to explain why the New York Stock
Exchange had nothing to do with the flash crash. “That’s when
a light went off,” said Danny Moses, of Seawolf Capital, a hedge
fund that specialized in stock market investments. He had heard
Brad and Ronan’s pitch. “Niederauer was saying, ‘Hey, have
confidence in us. It wasn’t us.’ Wait a minute: I never thought it
was you. Why should I be concerned that it was you? It was like
your kid walks into your house and says to you, ‘Dad, I didn’t
dent your car.’ Wait, there’s a dent in my car?”
After the flash crash, Brad no longer bothered to call investors
to set up meetings. His phone rang off the hook. “What the flash
crash did,” said Brad, “was it opened the buy side’s willingness
to understand what was going on. Because their bosses started
asking questions. Which meant that our telling the truth, and
explaining it to them, fit perfectly.”
A few months later, in September 2010, another strange,
albeit more obscure, market event occurred, this time in the
Chicago suburbs. A sleepy stock exchange called the CBSX,
which traded just a tiny fraction of total stock market volume,
announced that it was going to invert the usual system of fees
and kickbacks. It was now going to pay people to “take” liquid-
ity and charge people to “make” it. Once again, this struck Brad
as bizarre: Who would make markets on exchanges if they had
to pay to do it? But then the CBSX exploded with activity.
Over the next several weeks, for example, it handled a third of
RONAN’S PROBLEM
83
the total volume of the shares traded in Sirius, the satellite radio
company. Brad knew that Sirius was a favorite stock of HFT
firms — but he couldn’t understand why it was suddenly trading
in huge volume in Chicago. Obviously, when they saw they
could be paid to “take” on the CBSX, the big Wall Street bro-
kers all responded by reprogramming their routers so that their
customers’ orders were sent to the CBSX. But who was on the
other side of their trades, paying more than ever had been paid
for the privilege?
That’s when Ronan told Brad about a new company called
Spread Networks. Spread Networks, as it turned out, had tried
to hire Ronan to sell its precious line to high-frequency trad-
ers. They’d walked Ronan through their astonishing tunneling
project and their business plans. “I told them they were fucking
bananas,” said Ronan. “They said they were going to sell two
hundred of these things. I came up with a list of twenty-eight
firms who would potentially buy the line. Plus they were charg-
ing ten point six million dollars up front for five years’ worth of
service, and they wanted to pay me twelve grand for each one I
sold. Which is just an insult. You might as well ask me to blow
you while I’m doing it.”
Ronan mentioned this unpleasant experience to Brad, who
naturally said, “You’re telling me this nouP.” Ronan explained
that he hadn’t been able to mention Spread before because he
had signed a non-disclosure agreement with the company. The
agreement had expired that day, and so now he was free to dis-
close not only what Spread had done but for whom they had
done it: not just HFT firms like Knight and Citadel but also the
big Wall Street banks — Morgan Stanley, Goldman Sachs, and
others. “You couldn’t prove what these guys were doing was a
big deal, because they were so guarded about how much money
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they were making,” said Brad. “But you could see how big a
deal it was by how much they spent. And now the banks were
involved. I thought, Oh shit, this isn’t just HFT shops. This is
industry-wide. It’s systemic.”
Ronan offered an explanation for what had just happened on
the CBSX: Spread Networks had flipped its switch and turned
itself on just two weeks earlier. CBSX then inverted its pricing.
By inverting its pricing — by paying brokers to execute custom-
ers’ trades for which they would normally be charged a fee— the
exchange enticed the brokers to send their customers’ orders to
the CBSX so that they might be front-run back to New Jersey
by high-frequency traders using Spread Networks. The infor-
mation that high-frequency traders gleaned from trading with
investors in Chicago they could use back in the markets in New
Jersey. It was now very much worth it to them to pay the CBSX
to “make” liquidity. It was exactly the game they had played on
BATS, of enticing brokers to reveal their customers’ intentions
so that they might exploit them elsewhere. But racing a cus-
tomer order from Weehawken to other points in New Jersey was
hard compared to racing it from Chicago on Spread’s new line.
Spread was another piece of what was becoming a fantastically
elaborate puzzle. The team Brad was assembling at RBC didn’t
have all the pieces to the puzzle — not yet — but they had more
of them than anyone else willing to talk openly on the sub-
ject. The reactions of investors to what they already knew they
considered as simply more pieces of the puzzle. Every now and
then — perhaps 5 percent of the time — Brad or Ronan met some
investor who didn’t care to know about the puzzle, someone
who didn’t want to hear their story. Whenever Brad returned
from one of these meetings, he’d discover that the person to
whom he had just spoken depended, one way or another, on
RONAN’S PROBLEM
85
the revenues flowing to high-frequency traders. Every now and
again — maybe another 5 percent of the time — they met with
an investor who was completely terrified. “They knew so little,
and they’d be so scared inside their own firms that they’d rather
the meeting never happened,” said Brad. But most of the hun-
dreds of big-time investors with whom Brad and Ronan spoke
had the same reaction as T. Rowe Price’s Mike Gitlin: They
knew something was very wrong, but they didn’t know what,
and now that they knew they were outraged. “Brad was the
honest broker,” said Gitlin. “1 don’t know how many knew it,
but he was the only guy who would say it. He was saying, ‘I’m
here and I’m watching it and we’re a party to it and the whole
thing is rigged.’ He exposed people who were bad actors, and
a lot of people in this industry are afraid to do that. He was
saying, ‘This is just offensive.’ ” Vincent Daniel, the head strate-
gist at Seawolf, put it another way. He took a long look at this
unlikely pair — a Canadian Asian guy from this bank no one
cared about, and this Irish guy who was doing a fair impres-
sion of a Dublin handyman — who had just told him the most
incredible true story he had ever heard, and said, “Your biggest
competitive advantage is that you don’t want to fuck me.”
Trust on Wall Street was still — just — possible. The big inves-
tors who trusted Brad began to share whatever information they
could get their hands on from their other brokers — information
Brad was never meant to see. For instance, several demanded to
know from their other Wall Street brokers what percentage of the
trades executed on their behalf were executed inside the brokers’
dark pools. These dark pools contained the murkiest financial
incentives in the new stock market. Goldman Sachs and Credit
Suisse ran the most prominent dark pools. But every brokerage
firm strongly encouraged investors who wanted to buy or sell
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big chunks of stock to do so in that firm’s dark pool. In theory,
the brokers were meant to find the best price for their custom-
ers. If the customer wanted to buy shares in Chevron, and the
best price happened to be on the New York Stock Exchange, the
broker was not supposed to stick the customer with a worse price
inside their dark pool. But the dark pools were opaque. Their
rules were not published. No outsider could see what went on
inside them. It was entirely possible that a broker’s own traders
were trading against the customers in the dark pool: There were
no rules against it. And while the brokers often protested that
there were no conflicts of interest inside their dark pools, all the
dark pools exhibited the same strange property: A huge percent-
age of the customer orders sent into a dark pool were executed
inside the pool. Brad knew this because a handful of the world’s
biggest stock market investors had shared their information with
him — so that he might help them figure out what was going on.
It was hard to explain. A broker was expected to find the
best possible price in the market for his customer. The Goldman
Sachs dark pool — to take one example — was less than 2 percent
of the entire stock market. So why did nearly 50 percent of the
customer orders routed into Goldman’s dark pool end up being
executed inside that pool — rather than out in the wider market?
Most of the brokers’ dark pools constituted less than 1 percent of
the entire market, and yet somehow those brokers found the best
price for their customers between 15 and 60 percent of the time.
(So-called rates of internalization varied from broker to broker.)
And because the dark pool was not required to say exactly when
it had executed a trade, and the broker did not typically tell his
investors where it had executed a trade, much less the market
conditions at the moment of execution, the customer lived in
darkness. Even a giant investor like T. Rowe Price simply had to
RONAN’S PROBLEM
87
take it on faith that Goldman Sachs or Merrill Lynch had acted
in its interest, despite the obvious financial incentives not to do
so. As Mike Gitlin said, “It’s just very hard to prove that any
broker-dealer is routing the trades to someplace other than the
place that is best for you. You couldn’t SEE what any given bro-
ker was doing.” If an investor as large as T. Rowe Price, which
acted on behalf of millions of small investors, was unable to
obtain from its stockbrokers the information it needed to deter-
mine if the brokers had acted in their interest, what chance did
the little guy have?
In this environment, the effect of trying to help investors see
what was happening to their money was revolutionary. The
Royal Bank of Canada had never been anything more than the
most trivial player in the U.S. stock market. At the end of 2010,
Brad saw a report from Greenwich Associates, the firm used by
Wall Street banks to evaluate their standing in relation to their
peers. Greenwich Associates interviews the investors who use
Wall Street’s services and privately reports their findings to the
Wall Street firms. In 2009, RBC had — at number 19 — been far
down Greenwich Associates’ stock market rankings. At the end
of 2010, after only six months of Thor, RBC was ranked num-
ber 1. Greenwich Associates called RBC to ask what on earth
was going on within the bank. In the history of their rankings,
they said, they had never seen a firm jump more than three spots.
At the same time, this movement spawned by Brad Kat-
suyama’s unhappiness with Wall Street was starting to feel less
like a business than a cause. Brad was no radical. As he put it,
“There’s a difference between choosing a crusade and having it
thrust on you.” He’d never really thought all that much about
how he fit into the bigger picture, and certainly never consid-
ered himself a character upon a stage. He’d never run for stu-
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dent council. He’d never had anything to do with politics. “It’s
always seemed to me that the things you need to do to influ-
ence change had to do with glad-handing,” he said. “It just felt
so phony.” This didn’t feel phony. This felt like a situation in
which a person, through his immediate actions, might change
the world. After all, he was now educating the world’s biggest
money managers about the inner workings of the stock market,
which strongly suggested to him that no one else on Wall Street
was willing to teach them how their investment dollars were
being abused. The more he understood the inner workings of
the financial system, the better he might inform the investors,
big and small, who were being abused by that system. And the
more pressure they might bring to bear on the system to change.
The deep problem with the system was a kind of moral iner-
tia. So long as it served the narrow self-interests of everyone
inside it, no one on the inside would ever seek to change it, no
matter how corrupt or sinister it became — though even to use
words like “corrupt” and “sinister” made serious people uncom-
fortable, and so Brad avoided them. Maybe his biggest concern,
when he spoke to investors, was that he’d be seen as just another
nut with a conspiracy theory. One of the compliments that made
him happiest was when a big investor said, “Thank God, finally
there’s someone who knows something about high-frequency
trading who isn’t an Area 51 guy.” Because he wasn’t a radical,
it took him a while to figure out that fate and circumstance had
created for him a dramatic role, which he was obliged to play.
One night he actually turned to Ashley, now his wife, and said,
“It feels like I’m an expert in something that badly needs to be
changed. I think there’s only a few people in the world who can
do anything about this. If I don’t do something right now — me,
Brad Katsuyama — there’s no one to call.”
CHAPTER FOUR
TRACKING THE
PREDATOR
B y the end of 2010 they’d built a marketable weapon. The
weapon promised to defend investors in the U.S. stock
market from what appeared to be a new kind of mar-
ket predator. About that predator they knew surprisingly little.
Apart from Ronan, Brad knew no one from inside the world
of high-frequency trading. He had only a vague idea of that
world’s reach, or its political influence. From Ronan he knew
that the HFT firms enjoyed special relationships with the public
stock exchanges, but he knew nothing about their dealings with
the big Wall Street banks tasked with guarding the interests of
investors. Then again, many of the people who worked inside
the Wall Street banks seemed to have only the faintest idea of
what those banks were up to. If you worked for a big Wall Street
bank, the easiest way to find out what other banks were up to
was to seek out their employees who were looking for new jobs
and interview them. In the wake of the financial crisis, the too-
big-to-fail end of Wall Street was in turmoil, and Brad was able
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to talk to people who, just a few years before, would never have
considered working for the Royal Bank of Canada. By the time
he was finished picking their collective brains, he had spoken
to more than a hundred employees at too-big-to-fail banks but
hired only about thirty-five of them. “They all wanted jobs,”
he said. “It’s not that they wouldn’t tell me. It’s that they didn’t
know how their own electronic systems worked.”
The thread running through all these people, even the ones he
didn’t hire, was their fear and distrust of the system. John Schwab
was a curious case in point. Schwab’s father had been a firefighter
on Staten Island, like his father before him. “Every male on my
father’s side is a fireman,” Schwab said. “I wanted to do some-
thing more.” More meant getting a master’s in engineering from
the Stevens Institute of Technology, in Hoboken, New Jersey. In
the late 1990s he took a job at Banc of America Securities,* where
he rose to a position with an important-sounding title: Head of
New Products. His job description was more glamorous than his
job. John Schwab was the guy behind the scenes who handled
the boring details, like managing relations between the traders on
the floor and the tech geeks who built stuff for them, or ensuring
that the bank complied with new stock market regulations. He
routinely ranked in the top 1 percent of all employees in Banc of
America’s reviews of its personnel, but his status in a Wall Street
bank was akin to head butler to a British upper-class family. To
the grunts in the back office he might have seemed like a big
shot, but to the traders who made the money he did not.
* It is irritating to read about an American bank that insists on calling itself a banc. The
banc in this case was pushed to do so, as the securities divisions within American banks
(here, Bank of America) are prohibited by regulators from referring to themselves as
banks.
TRACKING THE PREDATOR
91
Whatever frustration this caused him he buried. Given an
excuse to feel loyalty for his company, he seized it. September
11, 2001, for instance. Schwab’s desk was in the North Tower
of the World Trade Center, on the eighty-first floor. By sheer
fluke he had been late to work that morning — the only day in
2001 he would report late to work — and he’d watched the first
plane hit, thirteen floors above his desk, from the window of a
distant bus. Several of his colleagues died that day, and so had
some Staten Island firemen he’d known. Schwab seldom spoke
of the event, but privately he believed that, had he been at his
desk when the plane hit, his instinct would have been to go up
the stairs rather than down them. The guilt he felt for not having
been on hand to help somehow became, in his mind, a debt he
owed to his colleagues and to his employer. Which is to say that
Schwab wanted to feel toward a Wall Street bank what a fireman
is meant to feel toward his company. “I thought I’d be at Banc of
America forever,” he said.
Then came the financial crisis, and, in 2008, the acquisition,
by Bank of America, of a collapsing Merrill Lynch. What hap-
pened next upended Schwab’s worldview. Merrill Lynch had
been among the most prolific creators of the very worst sub-
prime mortgage bonds. Had they been left to the mercy of the
market — had Bank of America not saved them — the Merrill
Lynch people would have been tossed out on the street. Instead,
right before their acquisition, they awarded themselves massive
bonuses that Bank of America wound up having to pay. “It was
incredibly unfair,” said Schwab. “It was incredibly unjust. My
stock in this company I helped to build for nine years goes into
the shitter, and these assholes pay themselves record bonuses. It
was a fucking crime.” Even more incredibly, the Merrill Lynch
people ended up in charge of Bank of America’s equity division
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and set about firing most of the people in it. A lot of those people
had been good, loyal employees of the bank. “Wall Street is cor-
rupt, I decided,” said Schwall afterwards. “There is no corporate
loyalty to employees.”
Schwall was one of the few Banc of America people who
kept his job: Merrill Lynch had no one to replace him. He hid
his true feelings, but he no longer trusted his employer. And he
sensed, for the first time in his career, that his employer did not
trust him. One day he sent himself an email from his personal
account to his work account — he was helping out some friends
who had been fired by the bank and who wanted to start a
small brokerage firm. His boss called him to ask him about it.
What the hell are they doing monitoring my incoming emails? Schwall
wondered.
His ability to monitor his superiors exceeded their ability
to monitor him, and he began to do it. “There was a lot of
unspoken animosity,” he said. He noticed the explosion of trad-
ing activity inside of Merrill Lynch’s dark pool fueled by high-
frequency traders. He saw that Merrill Lynch created a new
revenue line, to account for the money paid to them by high-
frequency trading firms for access to the Merrill Lynch dark
pool. He noticed that the guy who had built the Merrill Lynch
electronic trading platform was one of the highest-paid people
in all of Merrill Lynch — and he’d nevertheless quit to create a
company that would cater to HFT firms. He noticed letters sent
on bank letterhead to the Securities and Exchange Commission
arguing against further stock market regulation. He saved one in
which the bank’s lawyers wrote that “despite numerous changes
in recent years in both market structure and participant behav-
ior, the equity market is functioning well today.” One day he
heard a rumor that the Merrill people had assigned an analyst to
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93
produce a report to prove that Merrill’s stock market customers
were better off because of whatever happened inside Merrill’s
dark pool. There was apparently some controversy around this
report. Schwall filed that rumor away for later use.
Schwall wanted to think of himself as a guy who lived by a
few simple principles, a good soldier. After the financial cri-
sis he was more like the Resentful Butler. He had a taste for
asking complicated questions, and for tracking the answers into
whatever rabbit hole they might lead him. He had, in short, an
obsessive streak.
It wasn’t until after he’d hired Schwall away from Bank of
America to work for RBC that Brad noticed this side of Schwall.
He should have seen it before, simply from Schwall’s chosen role
on Wall Street: product manager. A product manager, to be any
good, had to be obsessive. The role had been spawned by the
widespread belief that traders didn’t know how to talk to com-
puter geeks and that computer geeks did not respond rationally
to big, hairy traders hollering at them. A product manager
stood between the two groups, to sort out which of the things
the traders wanted that were the most important and how
best to build them. For instance, an RBC stock market trader
might demand a button on his screen that said “Thor,” which
he could hit when he wanted Thor to execute his order to buy
stock. To design that button might require twenty pages of
mind-numbingly detailed specifications. That’s where Schwall
came in. “He goes into details that no one else will go into,
because for some reason that’s what he likes to do,” said Brad.
The first hint that Schwall’s obsession with detail might take a
sharp turn into some private cul-de-sac came in company meet-
ings. “He’d go off on complete tangents,” said Brad. “Semi-
related but outer space— type stuff.” Another way Brad saw how
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Schwall’s mind worked was in a fight that Schwall picked not
long after he started working at RBC. The bank had declined
an offer to serve as a lead sponsor for a charity called Wings
Over Wall Street. Wings Over Wall Street raised money to
combat amyotrophic lateral sclerosis (ALS) — Lou Gehrig’s dis-
ease. In response, and without explaining why, Schwall blasted
a system-wide email explaining the importance of ALS research
and encouraging all RBC employees to get behind Wings Over
Wall Street. The RBC executives who had made the original
decision understandably saw this rogue email as a political act
intended to undermine their authority. For no apparent reason,
Schwall had alienated a bunch of important people who had the
power to fire him.
Brad now found himself between his new, extremely valu-
able employee and a top RBC executive who wanted his scalp.
When pressed, Schwall finally explained to Brad that his mother
had just died of ALS. “And he hadn’t thought to mention it,”
said Brad. “He’d spent years trying to figure out how to help
his mother. The fact his mother died of the disease would have
won the argument, and he never mentions it. He said it would
have been underhanded and unprincipled.” Schwall’s problem
wasn’t an uncharming taste for corporate politics but a charming
ineptitude at playing them, Brad decided. (“Anyone who was
politically astute never would have done this.”) He neverthe-
less stumbled into politics often enough and played them badly
enough that Brad finally came up with a name for the resulting
mess: a Schwalling. “A Schwalling is when he does something
unintentionally idiotic that makes him look stupid,” said Brad.
All Schwall would say is, “I just sort of get crazy from time
to time.” He’d become obsessed with something, and his obses-
sions sent him on a trip to a place from which the journey’s ori-
TRACKING THE PREDATOR
95
gin could no longer be glimpsed. The result was a lot of activity
without an obvious motive.
Thor had triggered Schwab's private process. Thor, and what it
implied about the U.S. financial system, became Schwall’s great-
est obsession. Before Brad explained to him how Thor worked
and why, Schwab hadn’t thought twice about the U.S. stock
markets. After he met Brad, he was certain that the market at the
heart of capitalism was rigged. “As soon as you realize this,” he
said, “as soon as you realize that you are not able to execute your
orders because someone else is able to identify what you are try-
ing to do and race ahead of you to the other exchanges, it’s over,”
he said. “It changes your mind.” He stewed on the situation; the
longer he stewed, the angrier he became. “It really just pissed
me off,” he said. “That people set out this way to make money
from everyone else’s retirement account. I knew who was being
screwed, people like my mom and pop, and I became hell-bent
on figuring out who was doing the screwing.” He reconsidered
what he’d seen at Merrill Lynch after they had taken over Bank
of America’s stock trading department. He hunted down the
analyst who had done the controversial analysis of Merrill’s dark
pool, for instance. The analyst told him that he had found that
the dark pool was actually costing the customers (while profit-
ing Merrill Lynch), but that management did not want to hear it.
“They kept on telling him to change his report,” said Schwab.
“He was basically told that he had to find a different way to do
it to get the answer they needed.”
Early one Monday morning, in the summer of 2011, Brad had
a cab from Schwab. “He said, ‘Hey, I’m not coming in today,’ ”
recalls Brad. “And I said, ‘What’s going on?’ He just said, ‘Trust
me.’ Then he disappeared.”
The previous night Schwab had gone out into his backyard,
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with nothing but a cigar, a chair, and his iPad. “I had the belief
that some people were perpetuating a fraud. When you think
HFT, what do you think? You think nothing. You don’t have a
person. You don’t have a face. You think a computer. But there are
specific people behind this.” He’d started by Googling “front-
running” and “Wall Street” and “scandal.” What he was looking
for, at first, was the cause of the problem Thor had solved: How
was it legal for a handful of insiders to operate at faster speeds
than the rest of the market and, in effect, steal from investors?
He soon had his answer: Regulation National Market System.
Passed by the SEC in 2005 but not implemented until 2007,
Reg NMS, as it became known, required brokers to find the
best market prices for the investors they represented. The regu-
lation had been inspired by charges of front-running made in
2004 against two dozen specialists on the floor of the old New
York Stock Exchange — a charge the specialists settled by paying
a $241 million fine.
Up till then the various brokers who handled investors’ stock
market orders had been held to the loose standard of “best exe-
cution.” What that meant in practice was subject to interpreta-
tion. If you wanted to buy 10,000 shares of Microsoft at $30 a
share, and the broker went into the market and saw that there
were only 100 shares offered at $30, he might choose not to buy
those hundred shares and wait until more sellers turned up. He
had the discretion not to spook the market, and to play your
hand on your behalf as smartly as he could. After the brokers
abused the trust implicit in that discretion once too often, the
government took the discretion away. Reg NMS replaced the
loose notion of best execution with the tight legal one of “best
price.” To define best price, Reg NMS relied on the concept
of the National Best Bid and Offer, known as the NBBO. If
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97
an investor wished to buy 10,000 shares of Microsoft, and 100
shares were offered on the BATS exchange at $30 a share, while
the full 10,000 listed on the other twelve exchanges were offered
at $30.01, his broker was required to purchase the 100 shares
on Bats at $30 before moving on to the other exchanges. “It
mandated routing to more exchanges than you might otherwise
have to go to,” said Schwall. “And so it created more opportuni-
ties for people to front-run you.” The regulation also made it far
easier for high-frequency traders to predict where brokers would
send their customers’ orders, as they must send them first to the
exchange that offered the best market price.
That would have been fine but for the manner in which the
best market price was calculated. The new law required a mech-
anism for taking the measure of the entire market — for creat-
ing the National Best Bid and Offer — by compiling all the bids
and offers for all U.S. stocks in one place. That place, inside
some computer, was called the Securities Information Proces-
sor, which, because there is no such thing on Wall Street as too
many acronyms, became known as the SIP. The thirteen stock
markets piped their prices into the SIP, and the SIP calculated
the NBBO. The SIP was the picture of the U.S. stock market
most investors saw.
Like a lot of regulations, Reg NMS was well-meaning and
sensible. If everyone on Wall Street abided by the rule’s spirit,
the rule would have established a new fairness in the U.S. stock
market. The rule, however, contained a loophole: It failed to spec-
ify the speed of the SIP. To gather and organize the stock prices
from all the exchanges took milliseconds. It took milliseconds
more to disseminate those calculations. The technology used to
perform these calculations was old and slow, and the exchanges
apparently had little interest in improving it. There was no rule
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against high-frequency traders setting up computers inside the
exchanges and building their own, much faster, better cared for
version of the SIP. That’s exactly what they’d done, so well that
there were times when the gap between the high-frequency
traders view of the market and that of ordinary investors could
be twenty-five milliseconds, or twice the time it now took to
travel from New York to Chicago and back again.
Reg NMS was intended to create equality of opportunity in
the U.S. stock market. Instead it institutionalized a more perni-
cious inequality. A small class of insiders with the resources to
create speed were now allowed to preview the market and trade
on what they had seen.
Thus — for example — the SIP might suggest to the ordinary
investor in Apple Inc. that the stock was trading at 400-400.01.
The investor would then give his broker his order to buy 1,000
shares at the market price, or $400.01. The infinitesimal period
of time between the moment the order was submitted and the
moment it was executed was gold to the traders with faster con-
nections. How much gold depended on two variables: a) the gap
in time between the public SIP and the private ones and b) how
much Apple’s stock price bounced around. The bigger the gap
in time, the greater the chance that Apple’s stock price would
have moved; and the more likely that a fast trader could stick an
investor with an old price. That’s why volatility was so valuable
to high-frequency traders: It created new prices for fast traders
to see first and to exploit. It wouldn’t matter if some people in
the market had an early glimpse of Apple’s price if the price of
Apple’s shares never moved.
Apple’s stock moved a lot, of course. In a paper published in
February 2013, a team of researchers at the University of Cali-
fornia, Berkeley, showed that the SIP price of Apple stock and
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99
the price seen by traders with faster channels of market informa-
tion differed 55,000 times in a single day. That meant that there
were 55,000 times a day a high-frequency trader could exploit
the SIP-generated ignorance of the wider market. Fifty-five
thousand times a day, he might buy Apple shares at an outdated
price, then turn around and sell them at the new, higher price,
exploiting the ignorance of the slower-footed investor on either
end of his trades. And that was only the most obvious way a
high-frequency trader might use his advance view of the market
to make money.
Schwab already knew a lot about the boring nitty-gritty
details of Reg NMS, as he had been in charge of implementing
the new rule for the whole of Bank of America. He’d seen to
the bank’s need to build so-called smart order routers that could
figure out which exchange had the official best price of any
given stock (the NBBO) and send the customers’ orders to that
exchange. By complying with Reg NMS, he now understood,
the smart order routers simply marched investors into various
traps laid for them by high-frequency traders. “At that point I
just got very, very pissed off,” he said. “That they are ripping off
the retirement savings of the entire country through systematic
fraud and people don’t even realize it. That just drives me up the
fucking wall.”
His anger expressed itself in a search for greater detail. When
he saw that Reg NMS had been created to correct for the market
manipulations of the old NYSE specialists, he wanted to know:
How had that corruption come about? He began another search.
He discovered that the New York Stock Exchange specialists
had been exploiting a loophole in some earlier regulation —
which of course just led Schwab to ask: What event had led the
SEC to create that regulation? Many hours later he’d clawed his
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way back to the 1987 stock market crash, which, as it turned
out, gave rise to the first, albeit crude, form of high-frequency
trading. During the 1987 crash, Wall Street brokers, to avoid
having to buy stock, had stopped answering their phones, and
small investors were unable to enter their orders into the mar-
ket. In response, the government regulators had mandated the
creation of an electronic Small Order Execution System so that
the little guy’s order could be sent into the market with the
press of a key on a computer keyboard, without a stockbroker
first taking it from him on the phone. Because a computer was
able to transmit trades must faster than humans, the system was
soon gamed by smart traders, for purposes having nothing to
do with the little guy.* At which point Schwall naturally asked:
From whence came the regulation that had made brokers feel
comfortable not answering their phones in the midst of the 1987
stock market crash?
As it turns out, when you Google “front-running” and “Wall
Street” and “scandal,” and you are hell-bent on following the
search to its conclusion, the journey cannot be finished in an
evening. At five o’clock Monday morning Schwall finally went
back inside his house. He slept for two hours, then rose and
called Brad to tell him he wasn’t coming to work. Then he set
off for a Staten Island branch of the New York Public Library.
“There was quite a bit of vengeance on my mind,” he said. As
a high school junior Schwall had been New York City’s wres-
tling champion in the 119-pound division. “He’s the nicest guy
in the world most of the time,” said Brad. “But then sometimes
he’s not.” A streak of anger ran through him, and exactly where
* A year later, in 2012, Wall Street Journal reporter Scott Patterson would write an excel-
lent history of the early electronic traders called Dark Pools.
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it came from Schwall could not say, but he knew perfectly well
what triggered it: injustice. “If I can fix something and fuck
these people who are fucking the rest of this country, I’m going
to do it,” he said. The trigger for his most recent burst of feel-
ing was Thor, but if you had asked him on Wednesday morning
why he was still digging around the Staten Island library instead
of going to work, Schwall wouldn’t have thought to mention
Thor. Instead he would have said, “I am trying to understand
the origins of every form of front-running in the history of the
United States.”
Several days later he’d worked his way back to the late 1800s.
The entire history of Wall Street was the story of scandals, it
now seemed to him, linked together tail to trunk like circus
elephants. Every systemic market injustice arose from some
loophole in a regulation created to correct some prior injustice.
“No matter what the regulators did, some other intermedi-
ary found a way to react, so there would be another form of
front-running,” he said. When he was done in the Staten Island
library he returned to work, as if there was nothing unusual
at all about the product manager having turned himself into a
private eye. He’d learned several important things, he told his
colleagues. First, there was nothing new about the behavior they
were at war with: The U.S. financial markets had always been
either corrupt or about to be corrupted. Second, there was zero
chance that the problem would be solved by financial regula-
tors; or, rather, the regulators might solve the narrow problem
of front-running in the stock market by high-frequency traders,
but whatever they did to solve the problem would create yet
another opportunity for financial intermediaries to make money
at the expense of investors.
Schwall’s final point was more aspiration than insight. For
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the first time in Wall Street history, the technology existed that
eliminated entirely the need for financial intermediaries. Buyers
and sellers in the U.S. stock market were now able to connect
with each other without any need of a third party. “The way
that the technology had evolved gave me the conviction that
we had a unique opportunity to solve the problem,” he said.
“There was no longer any need for any human intervention.” If
they were going to somehow eliminate the Wall Street middle-
men who had flourished for centuries, they needed to enlarge
the frame of the picture they were creating. “I was so concerned
that we were talking about what we were doing as a solution to
high-frequency trading,” he said. “It was bigger than that. The
goal had to be to eliminate any unnecessary intermediation.”
BRAD FOUND IT odd that his product manager had set off to inves-
tigate the history of Wall Street scandal — it was a bit like an
offensive lineman choosing to skip practice to infiltrate the
opposing team’s locker room. But Schwab’s side career as a pri-
vate eye, at least at first, struck him as a harmless digression, of a
piece with Schwab’s tendency in meetings to go oft' on tangents.
“Once he gets on one of these bents it’s better just to let him go,”
said Brad. “That’s just him working eighteen-hour days instead
of fourteen-hour days.”
Besides, they now had far bigger problems. By the middle of
2011, Thor’s limitations were visible. “We had this meteoric rise
in our business the first year and then it flatlines,” said Brad. In
an open market, when customers were offered a new and bet-
ter product, they ditched their old product for it. Wall Street
banks weren’t subject to the usual open market forces. Inves-
tors paid Wall Street banks for all sorts of reasons: for research.
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to keep them sweet, to get private access to corporate execu-
tives, or simply because they had always done so. The way that
they paid them was to give them their trades to execute — that
is, they believed they needed to allocate some very large per-
centage of their trades to the big Wall Street banks simply to
maintain existing relations with them. RBC’s clients were now
routinely calling to say, “Hey, we love using Thor, but there is
only so much business we can do with you because we have to
pay Goldman Sachs and Morgan Stanley.”
The Royal Bank of Canada was running away with the title of
Wall Street’s most popular broker by peddling a tool whose only
purpose was to protect investors from the rest of Wall Street.
The investors refused to draw the obvious conclusion that they
should have a lot less to do with the rest of Wall Street. RBC
had become the number-one-rated stockbroker in America and
yet was still only the ninth best paid: They would never attract
more than a tiny fraction of America’s stock market trades, and
that fraction would never be enough to change the system. A
guy Ronan knew at the big high-frequency trading shop Citadel
called him one day and put the matter in a nutshell: I know what
you’re doing. It’s genius. And there’s nothing we can do about it. But
you are only two percent of the market.
On top of that, the big Wall Street banks, seeing RBC’s suc-
cess, were seeking to undermine it or at least to pretend to rep-
licate it. “The tech people at other firms are calling me and
saying, ‘I want to do Thor. How does Thor work?’ ” recalled
Allen Zhang. The business people at the banks were now call-
ing Ronan and Rob and offering them multiples of what they
earned at RBC to leave. The whole of Wall Street had been in
something like a two-year hiring freeze, and yet these big banks
were suggesting to Ronan — who had spent the past fifteen years
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unable to get his foot in the door of any bank — that they’d pay
him as much as $1.5 million to join them. Headhunters called
Brad and told him that, if he was willing to leave RBC for a
competitor, the opening bid was $3 million a year, guaranteed.
Just to keep his team in place, Brad arranged for RBC to create a
pool of money and set it aside: If the guys hung around for three
years, they would be handed the money and would wind up
being paid something closer to their market value. RBC agreed
to do it, probably because Brad did not ask for a piece of the
action himself and continued to work for far less than he could
have made elsewhere.
The bank’s marketing department proposed to Brad, as a way
to get some media attention for Thor, that he apply for a Wall
Street Journal Technology Innovation Award. Brad had never
heard of the Wall Street Journal’s Technology Innovation Awards,
but he thought that he might use the Wall Street Journal to tell
the world just how corrupt the U.S. stock market had become.
His bosses at RBC, when they got wind of his plans, wanted
him to attend a lot of meetings — to discuss what he might say
to the Wall Street Journal. They worried about their relationships
with other Wall Street banks and with the public exchanges.
“They didn’t want to ruffle anyone’s feathers,” says Brad. “There
was not a lot I couldn’t say in a small closed forum, but they
didn’t want me saying it openly.” He soon realized that, while
RBC would allow him to apply for awards, it would not let
him describe publicly what Thor had inadvertently exposed: the
manner in which HFT firms front-ran ordinary investors; the
conflict of interest that brokers had when they were being paid
by the exchanges to route orders; the conflict of interest the
exchanges had when they were being paid a billion dollars a year
by HFT firms for faster access to market data; the implications of
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an exchange paying brokers to “take” liquidity; that Wall Street
had found a way to bill investors without showing them the bill.
“I had about eight things I wanted to say to the Journal ,” said
Brad. “By the time I got through all these meetings, there was
nothing to say. I was only allowed to say one of them — that we
had found a way to route orders so they arrived at the exchanges
simultaneously.”
That was the problem with being RBC nice: It rendered you
incapable of going to war with nasty. Before Brad said any-
thing at all to the Wall Street Journal, RBC’s upper management
felt they needed to inform the U.S. regulators of what little he
planned to say. They asked Brad to prepare a report on Thor
for the SEC and then flew themselves down from Canada to
join him in a big meeting with the SEC’s Division of Trad-
ing and Markets staff. “It was more about not wanting them to
be embarrassed about not knowing about Thor than it was us
thinking they were going to do something about it,” Brad said.
He had no idea what a meeting at the SEC was supposed to be
like and prepared as if he were testifying before Congress. As
he read straight from the document he had written, the people
around the table listened, stoned-faced. “I was scared shitless,”
he said. When he was finished, an SEC staffer said, What you are
doing is not fair to high-frequency traders. You’re not letting them get out
of the way.
Excuse me? said Brad.
The SEC staffer argued that it was unfair that high-frequency
traders couldn’t post phony bids and offers on the exchanges to
extract information from actual investors without running the
risk of having to stand by them. It was unfair that Thor forced
them to honor the markets they claimed to be making. Brad just
looked at the guy: He was a young Indian quant.
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Then a second staffer, a much older guy, raised his hand and
said, If they don’t want to be on the offer they shouldn’t be there at all.
A lively argument ensued, with the younger SEC staffers tak-
ing the side of high-frequency trading and the older half tak-
ing Brad’s point. “There was no clear consensus,” said Brad.
“But it gave me a sense that they weren’t going to be doing
anything anytime soon.”* After the meeting, RBC conducted
a study, never released publicly, in which they found that more
than two hundred SEC staffers since 2007 had left their govern-
ment jobs to work for high-frequency trading firms or the firms
that lobbied Washington on their behalf. Some of these people
had played central roles in deciding how, or even whether, to
regulate high-frequency trading. For instance, in June 2010, the
associate director of the SEC’s Division of Trading and Markets,
Elizabeth King, had quit the SEC to work for Getco. The SEC,
like the public stock exchanges, had a kind of equity stake in the
future revenues of high-frequency traders.
The argument in favor of high-frequency traders had beaten
the argument against them to the U.S. regulators. It ran as fol-
lows: Natural investors in stocks, the people who supply capi-
tal to companies, can’t find each other. The buyers and sellers
of any given stock don’t show up in the market at the same
time, so they needed an intermediary to bridge the gap, to buy
from the seller and to sell to the buyer. The fully computerized
market moved too fast for a human to intercede in it, and so
the high-frequency traders had stepped in to do the job. Their
* “There’s a culture in the SEC of not getting into a dialogue with any individual who
comes in,” says a staffer who listened to Brad Katsuyama’s presentation. “They don’t
want to give any one person an unfair peek at the way the SEC thinks. But it’s a very
defensive culture. And there were people in the room who had written some of the rules
he was implicitly criticizing.”
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importance could be inferred from their activity: In 2005 a
quarter of all trades in the public stock markets were made
by HFT firms; by 2008 that number had risen to 65 percent.
Their new market dominance — so the argument went — was a
sign of progress, not just necessary but good for investors. Back
when human beings sat in the middle of the stock market, the
spreads between the bids and the offers of any given stock were
a sixteenth of a percentage point. Now that computers did the
job, the spread, at least in the more actively traded stocks, was
typically a penny, or one-hundredth of 1 percent. That, said the
supporters of high-frequency trading, was evidence that more
HFT meant more liquidity.
The arguments against the high-frequency traders hadn’t
spread nearly so quickly — at any rate, Brad didn’t hear them
from the SEC. A distinction cried out to be made, between
“trading activity” and “liquidity.” A new trader could leap into a
market and trade frantically inside it without adding anything of
value to it. Imagine, for instance, that someone passed a rule, in
the U.S. stock market as it is currently configured, that required
every stock market trade to be front-run by a firm called Scalp-
ers Inc. Under this rule, each time you went to buy 1,000 shares
of Microsoft, Scalpers Inc. would be informed, whereupon it
would set off to buy 1,000 shares of Microsoft offered in the
market and, without taking the risk of owning the stock for
even an instant, sell it to you at a higher price. Scalpers Inc. is
prohibited from taking the slightest market risk; when it buys,
it has the seller firmly in hand; when it sells, it has the buyer in
hand; and at the end of every trading day, it will have no posi-
tion at all in the stock market. Scalpers Inc. trades for the sole
purpose of interfering with trading that would have happened
without it. In buying from every seller and selling to every
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buyer, it winds up: a) doubling the trades in the marketplace
and b) being exactly 50 percent of that booming volume. It adds
nothing to the market but at the same time might be mistaken
for the central player in that market.
This state of affairs, as it happens, resembles the United States
stock market after the passage of Reg NMS. From 2006 to
2008, high-frequency traders’ share of total U.S. stock mar-
ket trading doubled, from 26 percent to 52 percent — and it has
never fallen below 50 percent since then. The total number of
trades made in the stock market also spiked dramatically, from
roughly 10 million per day in 2006 to just over 20 million per
day in 2009.
“Liquidity” was one of those words Wall Street people threw
around when they wanted the conversation to end, and for
brains to go dead, and for all questioning to cease. A lot of
people used it as a synonym for “activity” or “volume of trad-
ing,” but it obviously needed to mean more than that, as activ-
ity could be manufactured in a market simply by adding more
front-runners to it. To get at a useful understanding of liquidity
and the likely effects of high-frequency trading on it, one might
better begin by studying the effect on investors’ willingness to
trade once they sense that they are being front-run by this new
front-running entity. Brad himself had felt the effect: When the
market as displayed on his screens became illusory, he became
less willing to take risk in that market — to provide liquidity. He
could only assume that every other risk-taking intermediary —
every other useful market participant — must have felt exactly
the same way.
The argument for HFT was that it provided liquidity, but
what did this mean? “HFT firms go home flat every night,” said
Brad. “They don’t take positions. They are bridging an amount
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of time between buyers and sellers that’s so small that no one
even knows it exists.” After the market was computerized and
decimalized, in 2000, spreads in the market had narrowed — that
much was true. Part of that narrowing would have happened
anyway, with the automation of the stock market, which made
it easier to trade stocks priced in decimals rather than in frac-
tions. Part of that narrowing was an illusion: What appeared to
be the spread was not actually the spread. The minute you went
to buy or sell at the stated market price, the price moved. What
Scalpers Inc. did was to hide an entirely new sort of activity
behind the mask of an old mental model — in which the guy
who “makes markets” is necessarily taking market risk and pro-
viding “liquidity.” But Scalpers Inc. took no market risk.*
In spirit Scalpers Inc. was less a market enabler than a weird
sort of market burden. Financial intermediation is a tax on capi-
tal; it’s the toll paid by both the people who have it and the
people who put it to productive use. Reduce the tax and the
rest of the economy benefits. Technology should have led to a
reduction in this tax; the ability of investors to find each other
without the help of some human broker might have eliminated
the tax altogether. Instead this new beast rose up in the middle
of the market and the tax increased — by billions of dollars. Or
had it? To measure the cost to the economy of Scalpers Inc., you
needed to know how much money it made. That was not pos-
sible. The new intermediaries were too good at keeping their
* In early 2013, one of the largest high-frequency traders, Virtu Financial, publicly
boasted that in five and a half years of trading it had experienced just one day when
it hadn’t made money, and that the loss was caused by “human error.” In 2008, Dave
Cummings, the CEO of a high-frequency trading firm called Tradebot, told university
students that his firm had gone four years without a single day of trading losses. This sort
of performance is possible only if you have a huge informational advantage.
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profits secret * Secrecy might have been the signature trait of the
entities who now sat at the middle of the stock market: You had
to guess what they were making from what they spent to make
it. Investors who eyeballed the situation did not find reason for
hope. “There used to be this guy called Vinny who worked on
the floor of the stock exchange,” said one big investor who had
observed the market for a long time. “After the markets closed
Vinny would get into his Cadillac and drive out to his big house
in Long Island. Now there is the guy called Vladimir who gets
into his jet and flies to his estate in Aspen for the weekend. I
used to worry a little about Vinny. Now I worry a lot about
Vladimir.”
Apart from taking some large sum of money out of the market,
and without taking risk or adding anything of use to that mar-
ket, Scalpers Inc. had other, less intended consequences. Scalpers
Inc. inserted itself into the middle of the stock market not just as
an unnecessary middleman but as a middleman with incentives
to introduce dysfunction into the stock market. Scalpers Inc.
was incentivized, for instance, to make the market as volatile
as possible. The value of its ability to buy Microsoft from you
at $30 a share and to hold the shares for a few microseconds —
knowing that, even it the Microsoft share price began to fall, it
could turn around and sell the shares at $30.01 — was determined
by how likely it was that Microsoft’s share price, in those magi-
cal microseconds, would rise in price. The more volatile Micro-
soft’s share price, the higher Microsoft’s stock price might move
* A former employee of Citadel who also once had top secret security clearance at the
Pentagon says, “To get into the Pentagon and into my area, it took two badge swipes.
One to get into the building and one to get into my area. Guess how many badge swipes
it took me to get to my seat at Citadel? Five.”
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during those microseconds, and the more Scalpers Inc. would be
able to scalp. One might argue that intermediaries have always
profited from market volatility, but that is not really true. The
old specialists on the New York Stock exchange, for instance,
because they were somewhat obliged to buy in a falling market
and to sell in a rising one, often found that their worst days were
the most volatile days. They thrived in times of relative stability.
Another incentive of Scalpers Inc. is to fragment the market-
place: The more sites at which the same stocks changed hands,
the more opportunities to front-run investors from one site to
another. The bosses at Scalpers Inc. would thus encourage new
exchanges to open, and would also encourage them to place
themselves at some distance from each other. Scalpers Inc. also
had a very clear desire to maximize the difference between the
speed of their private view of the market and the view afforded
the wider public market. The more time that Scalpers Inc.
could sit with some investor’s stock market order, the greater
the chance that the price might move in the interim. Thus an
earnest employee of Scalpers Inc. would look for ways either to
slow down the public’s information or to speed up his own.
The final new incentive introduced by Scalpers Inc. was per-
haps the most bizarre. The easiest way for Scalpers Inc. to extract
the information it needed to front-run other investors was to
trade with them. At times it was possible to extract the necessary
information without having to commit to a trade. That’s what
the “flash order” scandal had been about: high-frequency trad-
ers being allowed by the exchanges to see other people’s orders
before anyone else, without any obligation to trade against them.
But for the most part, if you wanted to find out what some big
investor was about to do, you needed to do a little bit of it with
him. For instance, to find out that, say, T. Rowe Price wanted
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to buy 5 million shares of Google Inc., you needed to sell some
Google to T. Rowe Price. That initial market contact between
any investor and Scalpers Inc. was like the bait in a trap — a loss
leader. For Scalpers Inc., the goal was to spend as little as pos-
sible to acquire the necessary information — to make those initial
trades, the bait, as small as possible.
To an astonishing degree, since the implementation of Reg
NMS, the U.S. financial markets had evolved to serve the nar-
row interests of Scalpers Inc. Since the mid-2000s, the average
trade size in the U.S. stock market had plummeted, the markets
had fragmented, and the gap in time between the public view
of the markets and the view of high-frequency traders had wid-
ened. The rise of high-frequency trading had been accompanied
also by a rise in stock market volatility — over and above the
turmoil caused by the 2008 financial crisis. The price volatil-
ity within each trading day in the U.S. stock market between
2010 and 2013 was nearly 40 percent higher than the volatility
between 2004 and 2006, for instance. There were days in 2011
in which volatility was higher than in the most volatile days of
the dot-com bubble.
The financial crisis brought with it a great deal of stock mar-
ket volatility; perhaps people just assumed that there was sup-
posed to be an unusual amount of drama in the stock market
evermore. But then the financial crisis abated and the drama
remained. There was no good explanation for this, but Brad
now had a glimmer of one. It had to do with the way a front-
runner operates. A front-runner sells you a hundred shares of
some stock to discover that you are a buyer and then turns around
and buys everything else in sight, causing the stock to pop higher
(or the opposite, if you happen to be a seller). The Royal Bank of
Canada had tested the effects on stock market volatility of using
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Thor, which stymied front-runners, rather than the standard
order routers used by Wall Street, which did not. The sequential
cost-effective router responded to the kickbacks and fees of the
various exchanges and went to those exchanges first that paid
them the most to do so. The spray router — which, as its name
suggests, just sprayed the market and took whatever stock was
available, or tried to — did not make any effort to compel a stock
market order to arrive at the different exchanges simultaneously.
Every router, when it bought stock, tended to drive the price
of that stock a bit higher. But when the stock had settled — say,
ten seconds later — it settled differently with each router. The
sequential cost-effective router caused the share price to remain
higher than the spray router did, and the spray router caused it to
move higher than Thor did. “I have no scientific evidence,” said
Brad. “This is purely a theory. But with Thor the HFT firms are
trying to cover their losses. I’m short when I don’t want to be, so I
need to buy to cover, quickly.” The other two routers enabled HFT
to front-run, so they wound up being long the stock. “[With]
the other two, HFT is in a position to trade around a winning
position,” said Brad, “and they can do whatever they can do
to force the stock even higher.” (Or lower, if the investor who
triggered the activity is a seller.) They had, in those privileged
microseconds, the reckless abandon of gamblers playing with
house money.
The new choppiness in the public U.S. stock markets was
spreading to other financial markets, as they, too, embraced
high-frequency traders. It was what investors most noticed:
They were less and less able to buy and sell big chunks of stock
in a gulp. Their frustration with the public stock exchanges had
led the big Wall Street banks to create private exchanges: dark
pools. By the middle of 2011, roughly 30 percent of all stock
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market trades occurred off the public exchanges, most of them
in dark pools. The appeal of these dark pools — said the Wall
Street banks — was that investors could expose their big stock
market orders without fear that those orders would be exploited.
WHAT BOTHERED RICH Gates, at least at first, was the tone of
the pitch he was hearing from the big Wall Street banks. All
through 2008 and 2009 they would come to his office and tell
him why he needed their algorithms to defend himself in the
stock market. This algo is like a tiger that lurks in the woods and waits
for the prey and then jumps on it. Or: This algo is like an anaconda
in a tree. The algos had names like Ambush and Nighthawk and
Raider and Dark Attack and Sumo. Citi had one called Dagger,
Deutsche Bank had Sheer, and Credit Suisse had one named
Guerrilla, which came, in the bank’s flip-chart presentation,
with a menacing drawing of Che Guevara wearing a beret and
scowling. What the hell was that about? Their very names made
Rich Gates wary; he also didn’t like how loudly the brokers
selling them told him they’d come to protect him. Protect him
from what? Why did he need protection? From whom did he
need to be protected? “I’m immediately skeptical of people say-
ing they are looking out for my interests,” Gates said. “Espe-
cially on Wall Street.”
Gates ran a mutual fund, TFS Capital, that he had created in
1997 with friends from the University of Virginia. Fie liked to
think of himself as a hick, but in truth he was a keenly analytical
math geek in the perfectly pleasant Philadelphia suburb of West
Chester. He managed nearly $2 billion belonging to 35,000
small investors but still positioned himself, even in his own
mind, as an industry outsider. He believed that mutual funds
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were less often exercises in smart money management than in
creepy marketing, and that many of the people who ran mutual
funds should be doing something else with their lives. Back in
2007, to make this point, he dug out of a stack of league tables
America’s worst-performing mutual fund: the Phoenix Market
Neutral Fund. Over the prior decade, Gates’s firm had earned its
investors returns of 10 percent per year. Over that same period,
the Phoenix Market Neutral Fund had lost .09 percent a year for
its investors — the investors would have been better oft hopping
over the fence of the president of the Phoenix Market Neu-
tral Fund’s home and burying the money in his backyard. Gates
wrote a letter to the Phoenix president saying, in effect, You are
so obviously inept at managing money that you could do your investors
a favor by turning over all of your assets to me and letting me run them
for you. The president failed to reply.
The machismo of Wall Street’s algorithms, combined with
what struck Gates as a lot of nonsensical talk about the need
for trading speed, stirred his naturally suspicious mind. “I just
noticed a lot of bullshit,” he said. He and his colleagues devised a
test to see if there was anything in this new stock market to fear.
The test, specifically, would show him if, when he entered an
order into one of Wall Street’s dark pools, he wound up getting
ripped off by some unseen predator. He started by identifying
stocks that didn’t trade very often. Chipotle Mexican Grill, for
instance. He sent in an order to a single Wall Street dark pool
to buy that stock at the “mid-market” price. Say, for example,
that the shares of Chipotle Mexican Grill were trading at 100—
100.10. Gates would submit his bid to buy a thousand shares of
Chipotle at $100.05. There it would normally just sit until some
other investor came along and lowered his price from $100.10 to
$100.05. Gates didn’t wait for that to happen. Instead, a few sec-
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onds later, he sent a second order to one of the public exchanges,
to sell Chipotle at $100.01.
What should have happened next was that his order in the
dark pool should have been fdled at $100.01, the official new best
price in the market. He should have been able to buy from him-
self the shares he was selling at $100.01. But that’s not what hap-
pened. Instead, before he could blink his eye, he had made two
trades. He had bought Chipotle from someone inside the Wall
Street dark pool at $100.05 and sold it to someone else on the
public exchange for $100.01. He’d lost 4 cents by, in effect, trad-
ing with himself. Only he hadn’t traded with himself; some third
party had obviously used the sell order he had sent to the public
exchange to exploit the buy order he had sent to the dark pool.
Gates and his colleagues wound up making hundreds of such
tests, with their own money, in several Wall Street dark pools.
In the first half of 2010 there was only one Wall Street firm in
whose dark pool the test came back positive: Goldman Sachs. In
the Goldman dark pool, Sigma X, he got ripped off a bit more
than half the time he ran the test. As Gates traded in lightly
traded stocks, and high-frequency trading firms were over-
whelmingly interested in heavily traded ones, these tests would
have been vastly more likely to generate false negatives than false
positives. Still, he was a bit surprised that Goldman, and only
Goldman, seemed to be running a pool that allowed someone
else to front-run his orders to the public stock exchanges. He
called his broker at Goldman. “He said it wasn’t fair,” said Gates,
“because it wasn’t just them. He said, ‘It’s happening all over. It’s
not just us.’ ”
Gates was dutifully shocked. “When I first saw the results of
these tests, I thought: This obviously is not right. As far as he
could tell, no one seemed much to care that 35,000 small inves-
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tors could be so exposed to predation inside Wall Street’s most
prominent bank. “I’m amazed that people don’t ask the ques-
tions,” he said. “That they don’t dig deeper. If some schmuck
in West Chester, PA, can figure it out, I’ve got to believe other
people did, too.” Outraged, Gates called a reporter he knew
at the Wall Street Journal. The reporter came to see Gates’s tests
and seemed interested, but two months later there was still no
piece in the Journal — and Gates sensed that there might never
be. (Among other things, the reporter was uncomfortable men-
tioning Goldman Sachs by name.) At which point Gates noticed
that the Dodd-Frank Wall Street Reform and Customer Pro-
tection Act, soon to be passed, contained a whistle-blower pro-
vision. “I’m like, ‘Holy crap, I’m trying to out this anyway. If I
can get paid, too — great.’ ”
The people who worked in the SEC’s Division of Trading
and Markets were actually great — nothing like what the pub-
lic imagined. They were smart and asked good questions and
even spotted small mistakes in Gates’s presentation, which he
appreciated — though, as with Brad Katsuyama, they gave him
no idea how they might respond to the information he’d given
them. They wondered, shrewdly, exactly who was ripping off
investors in Goldman’s dark pool. “They wanted to know if
Goldman Sachs’s prop group was on the other side of the trade,”
said Gates. He had no answer for that. “They don’t tell you who
took the other side of the trade,” he said. All he knew was that
he’d been ripped off, in exactly the way you might expect to be
ripped off, when you can’t see the market trading in real time
and others can.
And that, at least for a few months, was that. “After I blew the
whistle, I laid low,” Gates said. “I just wanted to focus on our
business. I don’t get off throwing bombs.” Then came the flash
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crash, and the Wall Street Journal’s interest was rekindled. The
paper published a piece on Rich Gates’s tests — without men-
tioning Goldman Sachs by name. “I think it’s going to set the
world on fire,” said Gates. “It didn’t do anything. There are fif-
teen comments at the bottom of the piece on the Web, and all of
them are Russian mail order brides.” But the piece led a person
close to both the BATS exchange and Credit Suisse to get in
touch with Gates with a suggestion: Run your tests again, spe-
cifically on the BATS exchange and the Credit Suisse dark pool
called Crossfinder. Just to see. Toward the end of 2010, Gates ran
another round of tests.
Sure enough, he was able to get himself ripped off, in exactly
the same way he had been ripped off in the Goldman Sachs
dark pool — on the BATS exchange, and inside the Credit Suisse
dark pool, and in some other places, too. At Goldman Sachs,
however, the tests were now negative. “When we did it the
first time,” he said, “it worked at Goldman but nowhere else.
When we did it six months later it didn’t work at Goldman, but
it worked everywhere else.”
IN MAY 2011, the small team Brad had created — Schwall, Ronan,
Rob Park, a couple of others — sat around a table in Brad’s office,
surrounded by the applications of past winners of the Wall Street
Journal’s Technology Innovation Awards. As it turned out,
RBC’s marketing department had informed them of the awards
the day before submissions were due — so they were scrambling
to figure out in which of several categories they belonged, and
how to make Thor sound life-changing. “There were papers
everywhere,” said Rob. “No one sounded like us. There were
people who had, like, cured cancer.” “It was stupid,” said Brad,
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“there wasn’t even a category to put us into. I think we ended
up applying under Other .”
With the purposelessness of the exercise hanging in the air,
Rob said, “I just had a sick idea.” Rob’s idea was to license the
technology to one of the exchanges. (Schwall had patented Thor
for RBC.) The line between Wall Street brokers and exchanges
had blurred. The big Wall Street banks now ran their own pri-
vate exchanges. The stock exchanges, for their part, were making
a bid to become brokers. The bigger ones now offered a service
that enabled brokers to simply hand them their stock market
orders, which they would then route. To their own exchange, of
course, but also to others. The service was used mainly by small
regional brokerage firms that didn’t have their own routers, but
this brokerage-like service opened up, at least in Rob’s mind, a
new possibility. If just one of the exchanges was handed the tool
for protecting investors from market predators, the small brokers
from around the country might flock to it, and it might become
the mother of all exchanges.
“Screw that,” said Brad. “Let’s just create our own stock
exchange.”
“We just sat there for a while,” said Rob. “Kind of staring at
each other. Create your oum stock exchange. What does that even
mean?”
A few weeks later Brad flew to Canada and sold his bosses
on the idea of an RBC-led stock exchange. Then, in the fall of
2011, he canvassed a handful of the world’s biggest money man-
agers (Janus Capital, T. Rowe Price, BlackRock, Wellington,
Southeastern Asset Management) and some of its most influen-
tial hedge fund managers (David Einhorn, Bill Ackman, Daniel
Loeb). They all had the same reaction. They loved the idea of a
stock exchange that protected investors from Wall Street’s pred-
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ators. They also thought that a new stock exchange, to be cred-
ibly independent of Wall Street, could not be created by a Wall
Street bank. Not even a bank as nice as RBC. If Brad wanted to
create the mother of all stock exchanges, he would need to quit
his job and do it on his own.
The challenges were obvious. He’d need to find money. He’d
need to persuade a lot of highly paid people to quit their Wall
Street jobs to work for tiny fractions of their current salaries —
and possibly even supply the capital to pay themselves to work.
“I was asking: Can I get the people I need? How long can we
survive without getting paid? Will our significant others let us
do this?” He also needed to find out if the nine big Wall Street
banks that controlled nearly 70 percent of all stock market orders*
would be willing to send those orders to a truly safe exchange.
It would be far more difficult to start an exchange premised on
fairness if the banks that controlled the vast majority of the cus-
tomers’ orders were committed to unfairness.
For a surprisingly long time, Brad had reserved final judg-
ment about the biggest Wall Street banks. “I held out a degree
of hope that the people at [each] bank who handled the clients’
orders were removed from the prop group,” he said. His hope
sprang mainly from his own experience: At RBC, where he
handled the clients’ orders, he barely knew the prop traders and
had no idea what they were doing. There was a reason for this:
RBC had not created a dark pool, because Brad had killed the
idea. Still, he knew that each of the big Wall Street banks had its
own internal politics, and that there were people in each of them
* Those nine banks, in order of their (fairly evenly distributed) 2011 market share, from
highest to lowest: Credit Suisse, Morgan Stanley, Bank of America, Merrill Lynch,
Goldman Sachs, J.P. Morgan, Barclays, UBS, Citi, Deutsche Bank.
TRACKING THE PREDATOR
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who wanted to act in the long-term interests of their firms and
do the right thing by their customers. His hope was that some of
these people, in some of these places, had power.
John Schwall’s private investigations put an end to that hope.
By the fall of 2011 Schwab had become something like a con-
noisseur of the uses of Linkedln to find stuff out about people
in and around high-frequency trading. He’d put a face on high-
frequency trading, or rather two faces. “I began to anticipate
that certain people were in on the game,” said Schwab. “I’d
connect to them so that I could see their network. There were
maybe twenty-five guys I called kingpins — the people who
actually knew what was going on.” At the very top of the food
chain were a lot of white guys in their forties whose careers
could be traced back, one way or another, to the early elec-
tronic stock exchanges born of the regulations passed after the
crash of 1987 — Wall Street guys who might have some techni-
cal background but whose identity was more trader than pro-
gramming geek.
The new players in the financial markets, the kingpins of the
future who had the capacity to reshape those markets, were a
different breed: the Chinese guy who had spent the previous
ten years in American universities; the French particle physicist
from FERMAT lab; the Russian aerospace engineer; the Indian
PhD in electrical engineering. “There were just thousands of
these people,” said Schwab. “Basically all of them with advanced
degrees. I remember thinking to myself how unfortunate it was
that so many engineers were joining these firms to exploit inves-
tors rather than solving public problems.” These highly trained
scientists and technicians tended to be pulled onto Wall Street by
the big banks and then, after they’d learned the ropes, to move
on to smaller high-frequency trading shops. They behaved more
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like free agents than employees of a big corporation. In their
Linkedln profiles, for instance, they revealed all sorts of infor-
mation that their employers almost certainly would not want
revealed. Here Schwall stumbled upon the predator’s weakness:
The employees of the big Wall Street banks felt no more loyalty
toward the banks than the banks felt toward them.
The employees of Credit Suisse offered the clearest exam-
ple. Credit Suisse’s dark pool, Crossfmder, vied with Gold-
man Sachs’s Sigma X to be Wall Street’s biggest private stock
exchange. Credit Suisse’s biggest selling point to investors was
that it put their interests first and protected them from whatever
it was that high-frequency traders were doing. Back in October
2009, the head of Advanced Execution Services (AES) at Credit
Suisse, Dan Mathisson, had testified before a U.S. Senate Bank-
ing, Housing, and Urban Affairs Committee at a hearing on
dark pools. “The argument that dark pools are somehow part of
the high-frequency trading debate simply does not make sense,”
he’d said. “High-frequency traders make their money by digest-
ing publicly available information faster than others; dark pools
hide order information from everyone.”
That, Schwall thought, because Brad had explained it all to
him, was simply wrong. It was true that when, say, a pension fund
gave a Wall Street bank an order to buy 100,000 shares of Micro-
soft, and the Wall Street bank routed the order to the dark pool,
the wider world was not informed. But that was just the begin-
ning of the story. The pension fund did not know the rules of
the dark pool, and could not see how the buy order was handled
inside of it. The pension fund would not be able to say, for exam-
ple, whether the Wall Street bank allowed its own proprietary
traders to know of the big buy order, or if those traders had used
their (faster than the dark pool) market connections to front-run
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the order on the public exchanges. Even if the Wall Street bank
resisted the temptation to trade for itself against its own custom-
ers, there was virtually no chance they resisted the temptation to
sell access to the dark pool to high-frequency traders. The Wall
Street banks did not disclose which high-speed trading firms had
paid them for special access to their dark pools, or how much they
had paid, but selling that access was standard practice.
Raising, again, the obvious question: Why would anyone pay
for access to the customers’ orders inside a Wall Street bank’s dark
pool? The straight answer was that a customer’s stock market
order, inside a dark pool, was fat and juicy prey. The order was
typically large, and its movements were especially predictable:
Each Wall Street bank had its own detectable pattern for han-
dling orders. The order was also slow, because of the time it
was forced to spend inside the dark pool before accessing the
wider market. As Brad had put it, “You could front-run an
order in a dark pool on a bicycle.” The pension fund trying to
buy 100,000 shares of Microsoft could, of course, specify that
the Wall Street bank not take its orders to the public exchanges
at all but simply rest it, hidden, inside the dark pool. But an
order hidden inside a dark pool wasn’t very well hidden. Any
decent high-frequency trader who had paid for a special con-
nection to the pool would ping the pool with tiny buy and sell
orders in every listed stock, searching for activity. Once they’d
discovered the buyer of Microsoft, they’d simply wait for the
moment when Microsoft ticked lower on the public exchanges
and sell it to the pension fund in the dark pool at the stale,
higher “best” price (as Rich Gates’s tests had demonstrated).
It was riskless, larcenous, and legal — made so by Reg NMS.
The way Brad had described it, it was as if only one gambler
were permitted to know the scores of last week’s NFL games,
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with no one else aware of his knowledge. He places bets in the
casino on every game and waits for other gamblers to take the
other side of those bets. There’s no guarantee that anyone will
do so; but if they do, he’s certain to win.
In his investigation of the people who managed Credit Suisse’s
dark pool, one of the first things Schwab noticed was the guy
in charge of electronic trading: Josh Stampfli, who had joined
Credit Suisse after seven years spent working for Bernie Madoff.
(Madoff had pioneered the idea of paying brokers for the right to
execute the brokers’ customers’ orders, which should have told
people something but apparently did not.) This, of course, only
heightened Schwab’s suspicions, and sent him digging around
in old articles in trade journals about Credit Suisse’s dark pool.*
There he found references and allusions that made sense only
if Credit Suisse had planned, right from the start, to be deeply
involved with high-frequency trading firms. For instance, in
April 2008 a guy named Dmitri Galinov, a director and the
head of liquidity strategy at Credit Suisse, had told the Securi-
ties Technology Monitor that many of Credit Suisse’s “clients” had
placed computer servers in Weehawken, New Jersey, to be closer
to Credit Suisse’s dark pool. The only people who put servers
next to dark pools in Weehawken were Ronan’s old clients — the
high-frequency trading firms. No stock market investor went to
such lengths to shave microseconds off trading time.
“Client,” to Credit Suisse, appeared to Schwab to be a cat-
egory that included “high-frequency trading firms.” Schwab’s
suspicion that Credit Suisse wanted to service HFT while not
seeming to do so grew after he read an interview Dan Mathisson
gave to the New York Times in November 2009.
* Stampfli has not been charged with any wrongdoing.
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Q: Who are your clients at CrossFinder [sic] and how do they
benefit from using a dark pool as opposed to just going through
a broker and trading on the exchange?
A: Our clients are mutual funds, pension funds, hedge funds
and some other large broker-dealers, so it is always institutional
clients . . .
All the large high-frequency trading firms, Schwall knew,
were “broker-dealers.” They had to be, to gain the special access
they had to the public stock exchanges. So Mathisson had not
ruled out dealing with them. The only reason he would not
explicitly rule out dealing with them, Schwall assumed, was that
he was dealing with them.
The Linkedln searches became a new obsession. The former
MadofF employee’s profile led him to the people who worked for
the former MadofF employee, who led him to the people who
worked for them, and so on. Even as Credit Suisse tried to appear
as if it had nothing to do with high-frequency trading, its employ-
ees begged to differ. Schwall dug out dozens of examples of Credit
Suisse’s computer programmers boasting on their resumes about
“building high-frequency trading platforms” and “implementing
high-frequency trading strategy,” or of experience as a “quan-
titative trader on equity and equity derivatives: high-frequency
trading.” One guy explained that he had “managed on-boarding
of all high-frequency clients to Crossfinder.” Another said he had
built the Credit Suisse Crossfinder dark pool and now worked in
high-frequency trading market making. Credit Suisse claimed
that its dark pool had nothing to do with high-frequency trad-
ing, and yet it somehow employed, in and around its dark pool, a
mother lode of high-frequency trading talent.
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By the time he’d finished, Schwall had built the entire Credit
Suisse dark pool organization chart. “He’s got these people
charts,” said Brad incredulously. “It’s like one of those FBI
boards, with the drug kingpins.” Looking over Schwall’s charts
on Credit Suisse, the bank that went to the most trouble to sell
itself as safe to investors, Brad decided that the game was prob-
ably over inside all the big Wall Street banks. All of them, one
way or another, were probably using the unequal speeds in the
market to claim their share of the prey. He further assumed that
the big Wall Street banks must have stumbled upon his solution
to high-frequency front-running, and must have chosen not to
use it, because they had too great a stake in the profits generated
by that front-running. “It became very obvious to me why we
were the first to discover Thor, because we weren’t,” he said.
What that meant to me was that the problem was going to
be much, much harder to solve. It also told me why the clients
were so in the dark, because the clients rely on brokers for infor-
mation.” Creating an exchange designed to protect the prey
from the predator would mean starting a war on Wall Street —
between the banks and the investors they claimed to represent.
Schwall’s private investigations also revealed to Brad just how
little the technical people understood of their role in the financial
world. “It’s not like you are building a bridge connecting two
pieces of land,” he said. “You can’t see the effects of what you are
doing.” The openness with which the Credit Suisse technolo-
gists described their activities made him aware of a larger, almost
charming obliviousness. “I was totally shocked when John started
to pull out these resumes,” he recalled. “The banks had adopted
a policy of saying as little as possible about what they were actu-
ally doing. They’d fire people for being quoted in the newspaper,
but in their Linkedln pages those same people said whatever they
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wanted.” From the way the engineers described their roles in the
new financial system, he could see that they had no clue about
the injustices of that system. “It told me that these tech guys were
completely oblivious to what they were working on,” he said.
“They were tying these things they were working on — helping
the bank to make markets in their dark pools; building auto-
mated systems for the bank to use with its customers — in a way
you never would if you understood what the banks were doing.
It’s like saying on your Linkedln profile, ‘I have all the skills of a
robber and I know this one house intimately.’ ”
Schwall had started out looking for the villains who were
committing crimes against the life savings of ordinary Ameri-
cans, fully aware of their own villainy. He wound up finding,
mainly, a bunch of people who had no idea of the meaning
of their own lives. In his searches, Schwall noticed something
else, though at first he didn’t know what to make of it: A sur-
prisingly large number of the people pulled in by the big Wall
Street banks to build the technology for high-frequency trad-
ing were Russians. “If you went to Linkedln and looked at one
of these Russian guys, you would see he was linked to all the
other Russians,” said Schwall. “I’d go to find Dmitri and I’d also
find Misha and Vladimir and Tolstoy or whatever.” The Rus-
sians came not from finance but from telecom, physics, medical
research, university math departments, and a lot of other useful
fields. The big Wall Street firms had become machines for turn-
ing analytically minded Russians into high-frequency traders.
Schwall filed that fact away for later, as something perhaps worth
thinking about.
CHAPTER FIVE
PUTTING A FACE ON HFT
S ergey Aleynikov wasn’t the world’s most eager immi-
grant to America, or, for that matter, to Wall Street. He’d
left Russia in 1990, the year after the fall of the Berlin
Wall, but more in sadness than in hope. “When I was nineteen I
haven’t imagined leaving it,” he says. “I was very patriotic about
Russia. I cried when Brezhnev died. And I always hated English.
I thought I was completely incapable of learning languages.” His
problem with Russia was that its government wouldn’t allow
him to study what he wanted to study. He wasn’t religious in any
conventional sense, but he’d been born a Jew, which had been
noted on his Russian passport to remind everyone of the fact.
As a Jew he expected to be given especially difficult entrance
exams to university, which, if he passed them, would grant him
access to just one of two Moscow universities that were more
accepting of Jews, where he would study whatever the authori-
ties permitted Jews to study. Math, in Serge’s case. He’d been
willing to tolerate this state of affairs; however, as it happened.
PUTTING A FACE ON HFT
129
he’d also been born to program computers. He hadn’t laid hands
on a computer until 1986, when he was already sixteen. The
first thing he’d done was to write a program: He instructed the
computer to draw a picture of a sine wave. When the computer
actually followed his instructions, he was hooked. What hooked
him, he said, was “its detailed orientation. The way it requires
an ability to see the problem and tackle it from different angles.
It’s not just like chess, but like solving a particular problem in
chess. The more challenging problem is not to play chess but
to write the code that will play chess.” He found that coding
engaged him not just intellectually but also emotionally. “Writ-
ing a program is like giving birth to a child,” he said. “It is a
creation. Even though it is technical, it is a work of art. You get
this level of satisfaction.”
He applied to switch his major from mathematics to computer
science, but the authorities forbade it. “That is what tipped me
to accept the idea that perhaps Russia is not the best place for
me,” he says. “When they wouldn’t allow me to study computer
science.”
He arrived in New York City in 1990 and moved into a
dorm room at the 92nd Street Young Men’s and Young Wom-
en’s Hebrew Association, a sort of Jewish YMCA. Two things
shocked him about his new home: the diversity of the people on
the streets and the fantastic range of foods in the grocery stores.
He took photographs of the rows and rows of sausages in Man-
hattan and mailed them to his mother in Moscow. “I’d never
seen so many sausages,” he says. But once he’d marveled at the
American cornucopia, he stepped back from it all and wondered
just how necessary all of this food was. He read books about fast-
ing and the effects of various highly restrictive diets. “I decided
to look at it a little bit further and ask what is beneficial and what
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is not, he said. In the end he became a finicky vegetarian. “I
don’t think all the energy you gain comes from food,” he says.
“I think it comes from your environment.”
He’d come to America with no money at all, and no real idea
how to get it. He took a course on how to apply for a job. “It
was quite frightening,” he says. “I didn’t speak English, really,
and a resume was a totally alien concept.” His first interviewer
asked Serge to tell him about himself. “To a Russian mental-
ity, said Serge, that question means ‘Where are you born?’
‘Who are your siblings?’ ” Serge described for the man at great
length how he had come from a long line of Jewish scholars
and academics and nothing else. “He tells me I will hear from
him again. I never do.” But he had an obvious talent for pro-
gramming computers and soon found a job doing it, for $8.75 an
hour, in a New Jersey medical center. From the medical center
he landed a better job, in the Rutgers University computer sci-
ence department, where, through some complicated combina-
tion of jobs and grants, he was able to pursue a master’s degree.
After Rutgers he spent a few years working at Internet start-ups
until, in 1998, he received a job offer from a big New Jersey
telecom company called IDT. For the next decade he designed
computer systems and wrote the code to route millions of phone
calls each day to the cheapest available phone lines. When he
joined the company it had five hundred employees; by 2006 it
had five thousand, and he was its star technologist. That year a
headhunter called him and told him that there was fierce new
demand on Wall Street for his particular skill: writing code that
parsed huge amounts of information at great speed.
Serge knew nothing about Wall Street and was in no par-
ticular rush to learn about it. His singular talent was for mak-
ing computers go fast, but his own movements were slow and
PUTTING A FACE ON HFT
131
deliberate. The headhunter pressed upon him a bunch of books
about writing software on Wall Street, plus a primer on how to
make it through a Wall Street job interview, and told him that,
on Wall Street, he could make a lot more than the $220,000 a
year he was making at the telecom company. Serge felt flattered,
and liked the headhunter, but he read the books and decided
Wall Street wasn’t for him. He enjoyed the technical challenges
at the giant telecom and didn’t really feel the need to earn more
money. A year later, in early 2007, the headhunter called him
again. By this time IDT was in serious financial trouble; Serge
was beginning to worry that the management was running the
company into the ground. He had no savings to speak of. His
wife, Elina, was carrying their third child, and they’d need to
buy a bigger house. Serge agreed to interview with the Wall
Street firm that especially wanted to meet him: Goldman Sachs.
At least on the surface, Serge Aleynikov had the sort of life
people are said to come to America for. He’d married a pretty
fellow Russian immigrant and started a family with her. They’d
sold their two-bedroom Cape-style house in Clifton, New Jer-
sey, and bought a bigger colonial-style one in Little Falls. They
had a nanny. They had a circle of Russians they called their
friends. On the other hand, all Serge did was work, and his wife
had no real clue what that work involved; they weren’t actually
all that close to each other. He didn’t encourage people to get to
know him well or exhibit a great deal of interest in getting to
know them. He was acquiring a lot of possessions in which he
had very little interest. The lawn in Clifton was a fair example
of the general problem. When he’d gone hunting for his first
house, he’d been enchanted by the idea of having his very own
lawn. In Moscow such a thing was unheard of. The moment he
owned a lawn, he regretted it. (“A pain in the butt to mow.”) A
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Russian writer named Masha Leder, who knew the Aleynikovs
as well as anyone, thought of Serge as an exceptionally intel-
lectually gifted but otherwise typical Russian Jewish computer
programmer, for whom technical problems became an excuse
not to engage with the messy world around him. “All of Serge’s
life was some kind of mirage,” she said. “Or a dream. He was
not aware of things. He liked slender girls who loved to dance.
He married a girl and managed to have three kids with her
before he figures out he doesn’t really know her. He was work-
ing his ass off and she would spend the money he was mak-
ing. He would come home and she would cook him vegetarian
dishes. He was serviced, basically.”
And then Wall Street called. Goldman Sachs put Serge
through a series of telephone interviews, then brought him
in for a long day of face-to-face interviews. These he found
extremely tense, even a bit weird. “I was not used to seeing peo-
ple put so much energy into evaluating other people,” he said.
One after another, a dozen Goldman employees tried to stump
him with brain teasers, computer puzzles, math problems, and
even some light physics. It must have become clear to Goldman
(it was to Serge) that he knew more about most of the things he
was being asked than his interviewers did. At the end of the first
day, Goldman invited him back for a second day. He went home
and thought it over: He wasn’t all that sure he wanted to work
at Goldman Sachs. “But the next morning I had a competitive
feeling,” he says. “I should conclude it and try to pass it because
it’s a big challenge.”
He’d been surprised to find that in at least one way he fit in:
More than half the programmers at Goldman were Russians.
Russians had a reputation for being the best programmers on
Wall Street, and Serge thought he knew why: They had been
PUTTING A FACE ON HFT
133
forced to learn to program computers without the luxury of
endless computer time. Many years later, when he had plenty
of computer time, Serge still wrote out new programs on paper
before typing them into the machine. “In Russia, time on the
computer was measured in minutes,” he said. “When you write
a program, you are given a tiny time slot to make it work. Con-
sequently we learned to write the code in ways that minimized
the amount of debugging. And so you had to think about it a
lot before you committed it to paper. . . . The ready availability
of computer time creates this mode of working where you just
have an idea and type it and maybe erase it ten times. Good
Russian programmers, they tend to have had that one experi-
ence at some time in the past — the experience of limited access
to computer time.”
He returned for another round of Goldman’s grilling, which
ended in the office of a senior high-frequency trader — another
Russian, Alexander Davidovich. The Goldman managing direc-
tor had just two final questions for Serge, both designed to test
his ability to solve problems. The first: Is 3,599 a prime number?
Serge quickly saw that there was something strange about
3,599: It was very close to 3,600. He jotted down the following
equations:
3599 = (3600 - 1) = (60 2 - l 2 ) = (60 - 1) (60 + 1) = 59 x 61
3599 = 59 x 61
Not a prime number.
The problem wasn’t that difficult, but, as he put it, “it was
harder to solve the problem when you are anticipated to solve
it quickly.” It might have taken him as long as two minutes to
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finish. The second question the Goldman managing director
asked him was more involved, and involving. He described for
Serge a room, a rectangular box, and gave him its three dimen-
sions. He says there is a spider on the floor, and he gives me
its coordinates. There is also a fly on the ceiling, and he gives
me its coordinates as well. Then he asked the question: Calcu-
late the shortest distance the spider can take to reach the fly.”
The spider can’t fly or swing; it can only walk on surfaces. The
shortest path between two points was a straight line, and so,
Serge figured, it was a matter of unfolding the box, turning a
three-dimensional object into a two-dimensional surface, then
using the Pythagorean theorem to calculate the distances. This
took him several minutes to work out; when he was done,
Davidovich offered him a job at Goldman Sachs. His starting
salary plus bonus came to $270,000.
HE’D JOINED GOLDMAN at an interesting moment in the history of
both the firm and Wall Street. By mid-2007 Goldman’s bond
trading department was aiding and abetting a global financial
crisis, most infamously by helping the Greek government to rig
its books and disguise its debt, and by designing subprime mort-
gage securities to fail, so that they might make money by betting
against them. At the same time, Goldman’s equities department
was adapting to radical changes in the U.S. stock market— just as
that market was about to crash. A once sleepy oligopoly domi-
nated by Nasdaq and the New York Stock Exchange was rapidly
turning into something else. The thirteen public stock exchanges
in New Jersey were all trading the same stocks. Within a few
years there would be more than forty dark pools, two of them
owned by Goldman Sachs, also trading the same stocks.
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The fragmentation of the American stock market was fueled, in
part, by Reg NMS, which had also stimulated a huge amount of
stock market trading. Much of the new volume was generated not
by old-fashioned investors but by the extremely fast computers
controlled by the high-frequency trading firms. Essentially, the
more places there were to trade stocks, the greater the opportu-
nity there was for high-frequency traders to interpose themselves
between buyers on one exchange and sellers on another. This
was perverse. The initial promise of computer technology was
to remove the intermediary from the financial market, or at least
reduce the amount he could scalp from that market. The reality
turned out to be a windfall for financial intermediaries — of some-
where between $10 billion and $22 billion a year, depending on
whose estimates you wanted to believe. For Goldman Sachs, a
financial intermediary, that was only good news.
The bad news was that Goldman Sachs wasn’t yet making
much of the new money. At the end of 2008, they told their
high-frequency trading computer programmers that their trad-
ing unit had netted roughly $300 million. That same year, the
high-frequency trading division of a single hedge fund, Citadel,
made $1.2 billion. The HFT guys were already known for hid-
ing their profits, but a lawsuit between one of them, a Rus-
sian named Misha Malyshev, and his former employer, Citadel,
revealed that, in 2008, Malyshev had been paid $75 million in
cash. Rumors circulated — they turned out to be true — of two
guys who had left Knight for Citadel and guarantees of $20 mil-
lion a year each. A headhunter who sat in the middle of the
market and saw what firms were paying for geek talent says,
“Goldman had started to figure it out, but they really hadn’t
figured it out. They weren’t top ten.”
The simple reason Goldman wasn’t making much of the big
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money now being made in the stock market was that the stock
market had become a war of robots, and Goldman’s robots were
slow. A lot of the moneymaking strategies were of the winner-
take-all variety. When every player is trying to do the same
thing, the player who gets all the money is the one whose com-
puters can take in data and spit out the obvious response to it
first. In the various races being run, Goldman was seldom first.
That is why they had sought out Serge Aleynikov in the first
place: to improve the speed of their system. There were many
problems with that system, in Serge’s view. It wasn’t so much a
system as an amalgamation. “The code development practices at
IDT were much more organized and up-to-date than at Gold-
man,” he says. Goldman had bought the core of its system fifteen
years earlier in the acquisition of one of the early electronic trad-
ing firms, Hull Trading. The massive amounts of old software
(Serge guessed that the entire platform had as many as 60 mil-
lion lines of code in it) and fifteen years of fixes to it had created
the computer equivalent of a giant rubber-band ball. When one
of the rubber bands popped, Serge was expected to find it and
fix it.
Goldman Sachs often used complexity to advantage. The firm
designed complex subprime mortgage securities that others did
not understand, for instance, and then took advantage of the
ignorance they had introduced into the marketplace. The auto-
mation of the stock market created a different sort of complex-
ity, with lots of unintended consequences. One small example:
Goldman’s trading on the Nasdaq exchange. In 2007, Goldman
owned the (unmarked) building closest to Nasdaq. The build-
ing housed Goldman’s dark pool. When Serge arrived, tens of
thousands of messages per second were flying back and forth
between computers inside the two buildings. Proximity, he
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assumed, must offer Goldman Sachs some advantage — after all,
why else buy the building closest to the exchange? But when he
looked into it he found that, to cross the street from Goldman to
Nasdaq, a signal took 5 milliseconds, or nearly as much time as
it would take, a couple of years later, for a signal to travel on the
fastest network from Chicago to New York. “The theoretical
limit [of sending a signal] from Chicago to New York and back
is something like seven milliseconds,” said Serge. “Everything
more than that is the friction caused by man.” The friction could
be caused by physical distance — say, if the signal moving across a
street in Carteret traveled in something less direct than a straight
line. It could be caused by computer hardware. But it could also
be caused by slow, clunky software — and that was Goldman’s
problem. Their high-frequency trading platform was designed,
in typical Goldman style, as a centralized hub-and-spoke system.
Every signal sent was required to pass through the mother ship
in Manhattan before it went back out into the marketplace. “But
the latency [the 5 milliseconds] wasn’t mainly due to the physi-
cal distance,” says Serge. “It was because the traffic was going
through layers and layers of corporate switching equipment.”
Broadly speaking, there were three problems Serge had been
hired to solve. They corresponded to the three stages of an elec-
tronic trade. The first was to create the so-called ticker plant,
or the software that translated the data from the thirteen public
exchanges so that it could be viewed as a single stream. Reg
NMS had imposed on the big banks a new obligation: to take in
the information from all the exchanges in order to ensure that
they were executing customers’ orders at the official best market
price — the NBBO. If Goldman Sachs purchased 500 shares of
IBM at $20 a share on the New York Stock Exchange on behalf
of a customer without first taking the 100 shares of IBM offered
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at $19.99 on the BATS exchange, they’d have violated the regu-
lation. The easiest and cheapest solution for the big banks to this
problem was to use the combined data stream created by public
exchanges — the SIP. Some of them did just that. But to assuage
the concerns of their customers that the SIP was too slow and
offered them a dated view of the market, a few banks promised
to create a faster data stream — but nothing they created for cus-
tomers’ orders was as fast as what they created for themselves.
Serge had nothing to do with anything used by Goldman’s
customers. His job was to build the system that Goldman Sachs’s
own proprietary traders would use in their activities — and it
went without saying that it needed to be faster than anything
used by the customers. The first and most obvious thing he did
to make Goldman’s robots faster was exactly what he had done
at IDT to enable millions of phone calls to find their cheapest
route: He decentralized Goldman’s system. Rather than have
signals travel from the various exchanges back to the Goldman
hub, he set up separate mini-Goldman hubs inside each of the
exchanges. To acquire the information for its private ticker plant,
Goldman needed to place its computers as close as possible to the
exchange’s matching engine. The software that took the out-
put from the ticker plant and used it to figure out smart trades
in the stock market was the second stage of the process: Serge
rewrote a lot of that code to make it run faster. The third stage
was called “order entry.” As it sounds, this was the software that
sent those trades back out into the market to be executed. Serge
worked on that, too. He didn’t think of it this way, but in effect
he was building a high-frequency trading firm within Goldman
Sachs. The speed he created for Goldman Sachs could be used
for many purposes, of course. It could be used simply to execute
Goldman’s prop traders’ smart strategies as quickly as possible.
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It could also be used by Goldman’s prop traders to trade the
slow-moving customer orders in their own dark pool against
the wider market. The speed Serge gave them could be used, for
example, to sell Chipotle Mexican Grill to Rich Gates at a high
price in the dark pool while buying it from him at a lower price
on a public exchange.
Serge actually didn’t know what the speed was being used for
by Goldman’s prop traders. As he worked, he became aware of
a gulf in understanding between himself and his employer. The
people at Goldman with whom he dealt understood the effects
of what he did but not their deep causes. No one at Goldman
had a global view of the firm’s computer software, for instance:
He figured that out on the first day, when they asked him to look
into the code base and figure out how the different components
talked to each other. In doing so, he saw that there was shock-
ingly little documentation left behind by the people who had
written that code, and that no one at Goldman could explain
it to him. He, in turn, was not privy to the commercial effects
of his actions — in part, he sensed, because his superiors did not
want him to know them. “I think it is done intentionally,” he
said. “The less you know about how they make the money, the
better it is for them.”
But even if they had wanted him to know how the money was
made, it is unclear Serge would have cared to know. “I think the
engineering problems are much more interesting than the busi-
ness problems,” he says. “Finance is just who gets money. Does
it wind up in the right pocket or the left pocket? It just so hap-
pens that the companies that make money are the companies like
Goldman Sachs. You can’t really win in that game unless you
are one of these people.” He understood that Goldman’s quants
were forever dreaming up new trading strategies, in the form of
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algorithms, for his robots to execute, and that these traders were
meant to be extremely shrewd. He grasped further that “all their
algorithms are premised on some sort of prediction — predicting
something one second into the future.” But you needed only
to observe the 2008 stock market crash from inside of Gold-
man Sachs, as Serge had, to see that what seemed predictable
often was not. Day after volatile day in September 2008, Gold-
man’s supposedly brilliant traders were losing tens of millions
of dollars. “All of the expectations didn’t work,” recalls Serge.
“They thought they controlled the market, but it was an illu-
sion. Everyone would come into work and were blown away by
the fact that they couldn’t control anything at all. . . . Finance
is a gambling game for people who enjoy gambling.” He wasn’t
a gambler by nature. He preferred the deterministic world of
programming to the pseudo-deterministic world of speculation,
and he never fully grasped the connection between his work and
the Goldman traders’.
What Serge did know about Goldman’s business was that the
firm’s position in the world of high-frequency trading was inse-
cure. “The traders were always afraid of the small HFT shops,”
as he put it. He was making Goldman’s bulky, inefficient sys-
tem faster, but he could never make it as fast as a system built
from scratch, without the burden of 60 million lines of old code
underneath it. Or a system that, to change it in any major way,
did not require six meetings and signed documents from infor-
mational security officers. Goldman hunted in the same jungle
as the small HFT firms, but it could never be as quick or as
nimble as those firms: No big Wall Street bank could. The only
advantage a big bank enjoyed was its special relationship to the
prey: its customers. (As the head of one high-frequency trading
firm put it, “When one of these people from the banks inter-
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141
views with us for a job, he always talks about how smart his
algos are, but sooner or later he’ll tell you that without his cus-
tomer he can’t make any money.”)
After a few months working on the forty-second floor at
One New York Plaza, Serge came to the conclusion that the
best thing they could do with Goldman’s high-frequency trad-
ing platform was to scrap it and build a new one from scratch.
His bosses weren’t interested. “The business model of Goldman
Sachs was, if there is an opportunity to make money right away,
let’s do that,” he says. “But if there was something long-term,
they weren’t that interested.” Something would change in the
stock market — an exchange would introduce a new, complicated
rule, for instance — and that change would create an immediate
opportunity to make money. “They’d want to do it immedi-
ately,” says Serge. “But if you think about it, it’s just patching the
existing system constantly. The existing code base becomes an
elephant that’s difficult to maintain.”
That is how he spent the vast majority of his two years at
Goldman, patching the elephant. For their patching material
he and the other Goldman programmers resorted, every day,
to open source software — software developed by collectives of
programmers and made freely available on the Internet. The
tools and components they used were not specifically designed
for financial markets, but they could be adapted to repair Gold-
man’s plumbing. He discovered, to his surprise, that Goldman
had a one-way relationship with open source. They took huge
amounts of free software off the Web, but they did not return it
after he had modified it, even when his modifications were very
slight and of general, rather than financial, use. “Once I took
some open source components, repackaged them to come up
with a component that was not even used at Goldman Sachs,”
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he says. “It was basically a way to make two computers look
like one, so if one went down the other could jump in and
perform the task.” He’d created a neat way for one computer
to behave as the stand-in for another. He described the pleasure
ot his innovation this way: “It created something out of chaos.
When you create something out of chaos, essentially, you reduce
the entropy in the world.” He went to his boss, a fellow named
Adam Schlesinger, and asked if he could release it back into
open source, as was his inclination. “He said it was now Gold-
man’s property,” recalls Serge. “He was quite tense.”
Open source was an idea that depended on collaboration and
sharing, and Serge had a long history of contributing to it. He
didn’t fully understand how Goldman could think it was okay
to benefit so greatly from the work of others and then behave so
selfishly toward them. “You don’t create intellectual property,”
he said. “You create a program that does something.” But from
then on, on instructions from Adam Schlesinger, he treated
everything on Goldman Sachs’s servers, even if it had just been
transferred there from open source, as Goldman Sachs’s prop-
erty. (Later, at his trial, his lawyer flashed two pages of computer
code: the original, with its open source license on top, and a
replica, with the open source license stripped off and replaced by
the Goldman Sachs license.)
The funny thing was that Serge actually liked Adam Schles-
inger, and most of the other people he worked with at Goldman.
He liked less the environment the firm created for them to work
in. “Everyone lived for the year-end number,” he said. “You
get satisfied when the bonus is sizable and you get not satisfied
when the number is not. Everything there is very possessive.” It
made no sense to him the way people were paid individually for
achievements that were essentially collective achievements. “It
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143
was quite competitive. Everyone’s trying to show how good their
individual contribution to the team is. Because the team doesn’t
get the bonus, the individual does.”
More to the point, he felt that the environment Goldman
created for its employees did not encourage good programming,
because good programming required collaboration. “Essentially
there was very minimal connections between people,” he says.
“In telecom you usually have some synergies between people.
Meetings when people exchange ideas. They aren’t under stress
in the same way. At Goldman it was always, ‘Some component is
broken and we’re losing money because of it. Fix it now.’ ” The
programmers assigned to fix the code sat in cubicles and hardly
spoke to one another. “When two people wanted to talk they
wouldn’t just do it out on the floor,” says Serge. “They would go
to one of the offices around the floor and close the door. I never
had that experience in telecom or academia.”
By the time the financial crisis hit, Serge had a reputation
of which he himself was unaware: He was known to corpo-
rate recruiters outside Goldman as the best programmer in the
firm. “There were twenty guys on Wall Street who could do
what Serge could do,” says a headhunter who recruits often for
high-frequency trading firms. “And he was one of the best,
if not the best.” Goldman also had a reputation in the mar-
ket for programming talent— for keeping its programmers in
the dark about their value to the firm’s trading activities. The
programmer types were different from the trader types. The
trader types were far more alive to the bigger picture, to their
context. They knew their worth in the marketplace down to
the last penny. They understood the connection between what
they did and how much money was made, and they were good
at exaggerating the importance of the link. Serge wasn’t like
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that. He was a little-picture person, a narrow problem solver.
“1 think he didn’t know his own value,” says the recruiter.
“He compensated for being narrow by being good. He was
that good.”
Given his character and his situation, it’s hardly surprising
that the market kept finding Serge Aleynikov and telling him
what he was worth, rather than the other way around. A few
months into his new job, headhunters were calling him every
other week. A year into his new job, he had an offer from UBS,
the Swiss bank, and a promise to bump up his salary to $400,000
a year. Serge didn’t particularly want to leave Goldman Sachs
just to go and work at another big Wall Street firm, and so when
Goldman offered to match the offer, he stayed. But in early 2009
he had another call, with a very different kind of offer: to cre-
ate a trading platform from scratch for a new hedge fund run by
Misha Malyshev.
The prospect of creating a new platform, rather than con-
stantly patching an old one, excited him. Plus Malyshev was
willing to pay him more than a million dollars a year to do it,
and he suggested that they might even open an office for Serge
near his home in New Jersey. Serge accepted the job offer and
then told Goldman he was leaving. “When I put in the resigna-
tion letter,” he said, “everyone comes to me one by one. The
common perception was that if they had the right opportunity
to quit Goldman they would do that in no time.” Several hinted
to him how much they would like to join him at his new firm.
His bosses asked him what they could do to persuade him to
stay. “They were trying to pursue me into this monetary discus-
sion,” says Serge. “I told them it wasn’t the money. It was the
chance to build a new system from the ground up.” He missed
his telecom work environment. “Whereas at IDT I was really
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seeing the results of my work, here you had this monstrous sys-
tem and you are patching it right and left. No one is giving you
the whole picture. I had a feeling no one at Goldman really
knows how it works as a whole, and they are just uncomfortable
admitting that.”
He agreed to hang around for six weeks and teach other Gold-
man people everything he knew, so that they could continue
to find and fix the broken bands in their gigantic rubber ball.
Four times in the course of that last month he mailed himself
source code he was working on. The files contained a lot of
open source code he had worked with, and modified, over the
past two years, mingled with code that wasn’t open source but
was obviously proprietary to Goldman Sachs. He hoped to dis-
entangle one from the other in case he needed to remind him-
self how he had done what he had done with the open source
code; he might need to do it again. He sent these files the same
way he had sent himself files nearly every week since his first
month on the job at Goldman. “No one had ever said a word
to me about it,” he says. He pulled up his browser and typed
into it the words: “free subversion repository.” Up popped a list
of places that stored code for free and in a convenient fashion.
He clicked the first link on the list. To find a place to send the
code took about eight seconds. And then he did what he had
always done since he’d first started programming computers: He
deleted his bash history — the commands he had typed into his
own Goldman computer keyboard. To access the computer, he
was required to type his password. If he didn’t delete his bash
history, his password would be there to see, for anyone who had
access to the system.
It wasn’t an entirely innocent act. “I knew that they wouldn’t
be happy about it,” he said, because he knew their attitude was
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that anything that happened to be on Goldman’s servers was the
wholly owned property of Goldman Sachs — even when Serge
himself had taken that code from open source. When asked how
he felt when he did it, he says, “It felt like speeding. Speeding
in the car.”
FOR MUCH OF the flight from Chicago he’d slept. Leaving the
plane, he noticed three men in dark suits waiting in the alcove
of the Jetway reserved for baby strollers and wheelchairs. They
confirmed his identity, explained that they were from the FBI,
handcuffed him, searched his pockets, removed his backpack,
told him to remain calm, and then walled him oft' from the
other passengers. This last act was no great feat. Serge was
six feet tall but weighed roughly 140 pounds: To hide him
you needed only to turn him sideways. He resisted none of
these actions, but he was genuinely bewildered. The men in
black refused to tell him his crime. He tried to guess it. His
first guess was that they’d gotten him mixed up with some
other Sergey Aleynikov. Next it occurred to him that his new
employer, Misha Malyshev, then being sued by Citadel, might
have done something shady. Wrong on both counts. It wasn’t
until the plane had emptied and they’d escorted him into
Newark Airport that they told him his crime: stealing com-
puter code owned by Goldman Sachs.
The agent in charge of the case, Michael McSwain, was new
to law enforcement. Oddly enough, he’d spent twelve years,
until 2007, working as a currency trader on the Chicago Mer-
cantile Exchange. He and others like him had been put out of
business by Serge and people like him — or, more exactly, by the
computers that had replaced the traders on the floors of every
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U.S. exchange. It wasn’t an accident that McSwain’s career on
Wall Street ended the same year that Serge’s began.
McSwain marched Serge into a black town car and drove him
to the FBI building in lower Manhattan. After making a show
of stashing his gun, McSwain led him into a tiny interrogation
room, handcuffed him to a rod on the wall, and, finally, read
him his Miranda rights. Then he explained what he knew, or
thought he knew: In April 2009 Serge had accepted a job at a
new high-frequency trading shop, Teza Technologies, but had
remained at Goldman for the next six weeks. Between early
April and June 5, when Serge left Goldman for good, he sent
himself, through the so-called subversion repository, 32 mega-
bytes of source code from Goldman’s high-frequency stock trad-
ing system. McSwain clearly found it damning that the website
Serge used was called a subversion repository, and that it was
in Germany. He also seemed to think it significant that Serge
had used a site not blocked by Goldman Sachs, even after Serge
tried to explain to him that Goldman did not block any sites
used by its programmers but merely blocked its employees from
porn sites and social media sites and suchlike. Finally, the FBI
agent wanted him to admit that he had erased his bash history.
Serge tried to explain why he always erased his bash history, but
McSwain had no interest in his story. “The way he did it seemed
nefarious,” the FBI agent would later testify.
All of which was true, as far as it went, but, to Serge, that
didn’t seem very far. “I thought it was like, crazy, really,” he
says. “He was stringing these computer terms together in ways
that made no sense. He didn’t seem to know anything about
high-frequency trading or source code.” For instance, Serge had
no idea where the subversion repository was physically located.
It was just a place on the Internet used by developers to store the
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code they were working on. “The whole point of the Internet
is to abstract the physical location of the server from its logi-
cal address,” he said. To Serge, McSwain sounded like a man
repeating phrases that he’d heard from others but that to him
actually meant nothing. “There is a game in Russia called Bro-
ken Phone,” he said — a variation on the American game Tele-
phone. “It felt like he was playing that.”
What Serge did not yet know was that Goldman had dis-
covered his downloads — of what appeared to be the code they
used for their proprietary high-speed stock market trading — -just
a few days earlier, even though Serge had sent himself the first
batch of code months ago. They’d called the FBI in haste and
had put McSwain through what amounted to a crash course in
high-frequency trading and computer programming. McSwain
later conceded that he didn’t seek out independent expert advice
to study the code Serge Aleynikov had taken, or seek to find
out why he might have taken it. “I relied on statements from
Goldman employees,” he said. He had no idea himself of the
value of the stolen code (“representatives from Goldman told
me it was worth a lot of money”), or if any of it was actually
all that special (“representatives of Goldman Sachs told us there
were trade secrets in the code”). The agent noted that the Gold-
man files were on both the personal computer and the thumb
drive that he’d taken from Serge at Newark Airport, but he
failed to note that the files remained unopened. (If they were so
important, why hadn’t Serge looked at them in the month since
he’d left Goldman?) The FBI’s investigation before the arrest
consisted of Goldman explaining some extremely complicated
stuff to McSwain that he admitted he did not fully understand —
but trusted that Goldman did. Forty-eight hours after Goldman
called the FBI, McSwain arrested Serge. Thus the only Gold-
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149
man Sachs employee arrested by the FBI in the aftermath of
a financial crisis Goldman had done so much to fuel was the
employee Goldman asked the FBI to arrest.
On the night of his arrest, Serge waived his right to call a
lawyer. Fie called his wife, told her what had happened, and said
that a bunch of FBI agents were on the way to their home to
seize their computers, and to please let them in, although they
had no search warrant. Then he sat down and politely tried to
clear up the confusion of this FBI agent who had arrested him
without an arrest warrant. “Flow could he figure out if this was
a theft if he didn’t understand what was taken?” he recalls having
asked himself. What he’d done, in his view, was trivial; what he
stood accused of — violating both the Economic Espionage Act
and the National Stolen Property Act — did not sound trivial at
all. Still, he thought that it the agent understood how computers
and the high-frequency trading business actually worked, he’d
apologize and drop the case. “The reason I was explaining it to
him was to show that there was nothing there,” he said. “Fie
was completely not interested in the content of what I am say-
ing. He just kept saying to me, ‘If you tell me everything, I’ll
talk to the judge and he’ll go easy on you.’ It appeared they had
a very strong bias from the very beginning. They had goals they
wanted to fulfill. One was to obtain an immediate confession.”
The chief obstacle to the FBI’s ability to extract his confes-
sion, oddly, wasn’t Serge’s willingness to provide it but its own
agent’s ignorance of the behavior to which Serge was attempting
to confess. “In the written statement he was making some very
obvious mistakes, computer terms and so on,” recalled Serge.
“I was saying, ‘You know, this is not correct.’” Serge patiently
walked the agent through his actions. At 1:43 in the morning on
July 4, after five hours of discussion, McSwain sent a giddy one-
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line email to the U.S. Attorney’s office: “Holy crap he signed a
confession.”
Two minutes later, he dispatched Serge to a cell in the Metro-
politan Detention Center. The prosecutor, Assistant U.S. Attor-
ney Joseph Facciponti, argued that Serge Aleynikov should be
denied bail. The Russian computer programmer had in his pos-
session computer code that could be used “to manipulate mar-
kets in unfair ways.” The confession Serge had signed, scarred by
phrases crossed out and rewritten by the FBI agent, later would
be presented by prosecutors to a jury as the work of a thief who
was being cautious, even tricky, with his words. “That’s not
what happened,” said Serge. “The document was being crafted
by someone with no previous expertise in the matter.”
Sergey Aleynikov’s signed confession was the last anyone heard
from him, at least directly. He declined to speak to reporters or
testify at his trial. He had a halting manner, a funny accent, a
beard, and a physique that looked as if it had been painted by El
Greco: In a lineup of people chosen randomly from the streets,
he was the guy most likely to be identified as the Russian spy, or
a character from the original episodes of Star Trek. In technical
discussions he had a tendency to speak with extreme precision,
which was great when he was dealing with fellow experts but
mind-numbing to a lay audience. In the court of U.S. public
opinion, he wasn’t well suited to defend himself, and so, on the
advice of his attorney, he didn’t. He kept his long silence even
after he was sentenced, without the possibility of parole, to eight
years in a federal prison.
CHAPTER SIX
HOW TO TAKE BILLIONS
FROM WALL STREET
R onan didn’t intend to tell his father exactly how much
money he made, or anything else that sounded like boast-
ing, but he wanted him to know he needn’t worry about
his son any longer. For Christmas, in 2011, he’d fly back to
Ireland, as he did every year, only this year he’d travel toward
a conversation. He felt no particular attachment to the place.
“I don’t belong there at all,” he said. “There’s fucking fat kids
everywhere. When I was growing up there was no fat kids. It’s
lost its charm.” He missed his family, nothing more. When he
arrived at their house in the Dublin suburbs, his parents would
be waiting with a list of their stuff that needed to be repaired or
reprogrammed. After he’d rebooted their computer, or recap-
tured their satellite signal, he’d sit down with them and have this
talk. “American parents get into their fucking kids’ business,”
said Ronan. “In Ireland they don’t. They mind their own fuck-
ing business.” His father still had no clear idea what he did for a
living, or, for that matter, why a big Wall Street bank would find
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him useful. “He didn’t think I was a fucking teller or something.
But if I said to my dad, ‘I’m a trader,’ he’d say, ‘What the fuck do
you know about trading?’ ” His life was his life, theirs was theirs.
“My mom and dad, I know they love me. It’s just Irish love. And
I just kinda wanted him to know I was legit in this business. It
was semi to set him at ease. I didn’t want him to think I was
putting the family in jeopardy.”
Ireland’s economy had collapsed three years earlier, under the
weight of a lot of American-style financial machinations and bad
advice from American financiers. Many of Ronan’s childhood
friends were still out of work. It didn’t seem like the best time to
be taking a risk. Just days before Ronan was to fly back to Ire-
land, however, Brad Katsuyama had pulled him into a meeting
with John Schwall and Rob Park. Brad had wanted to know, if
he left RBC to create a new stock exchange, who might leave
with him. They’d taken turns answering the same question: You
in? On some level, Ronan could not believe what he was hear-
ing as he listened to the sound of his own voice: He’d spent his
entire career trying to get a job on Wall Street, and now that he
finally had one, the guy who had given it to him was asking him
to throw it away. On another level, the question answered itself.
“Too much was riding on me,” he said. “And I felt like I owed
Brad. He was the one who gave me a chance. I trusted him: He’s
not a fucking idiot.”
By the end of 2011, there was something else on Ronan’s
mind, too. He’d now seen Wall Street from the inside. It wasn’t
as persuasive to him as he had expected it to be. “It’s like if I stay
here I’ll become full of shit,” he said.
They were all very much in; what they were in for was less
clear. Until they found someone willing to pay for the building
of a new stock exchange, they couldn’t very well quit their jobs to
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153
do it. Ronan’s commitment to Brad was less a promise of imme-
diate action than a promissory note to be cashed at some point in
the indefinite future. But they did have a goal: to restore fairness
to the U.S. stock market — for the first time in Wall Street his-
tory, perhaps, to institutionalize fairness. And they had a rough
idea: to deploy Thor as the backbone of a strange new kind of
stock exchange, to which brokers could send stock market orders
so that Thor might route them to all the other exchanges. And
yet none of them, least of all Ronan, believed that Thor alone
could change the stock market, mainly because they doubted
that the big brokerage firms would hand over their most valu-
able commodity (their customers’ stock market orders) to any
third party to execute. They also suspected that other forms of
unfairness plagued the market, problems that Thor didn’t begin
to address. “I give what we have right now a ten percent chance
of working,” Ronan told his colleagues. “But with the four of us
I give us a seventy percent chance of figuring it out.”
After he left Brad’s office, Ronan realized that the talk he
wanted to have with his father had changed: He needed his
father’s advice. He’d already taken one big risk, when he had
quit a telecom job in which he’d made nearly half a million a
year for a Wall Street job that paid him a third of that. It had
panned out: RBC had just handed him a bonus of nearly a mil-
lion bucks and was asking him if he would like to run the more
lucrative half of their stock market trading operation. (“They
told me I could name my price.”) As his plane dipped toward
the Irish coast, he wanted to know if he was out of his mind to
quit his $910,000-a-year job for one that paid $2,000 a month —
money that would quite possibly be paid to him out of funds he
himself invested in the new company. His father might not care
to know the details, but he’d grasp the gist of his predicament.
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“I wanted to ask him: ‘Is there a time when you stop rolling the
dice?’ I didn’t know if RBC was that time.” But when he finally
sat his father down, Ronan realized he couldn’t explain even the
gist of his predicament unless he confessed the size of his bonus.
“When I was telling him I’d made nine hundred and ten thou-
sand dollars he about had a fucking heart attack,” said Ronan. “I
mean, he doubled over in his chair.”
At length his father recovered, then looked up at his son and
said, “You know what, Ro, your risks seem to have paid off so
far. Why the fuck not?”
Ronan landed back in New York on Tuesday, January 3,
2012, turned on his BlackBerry, and watched the new messages
flood in. The first was from Brad, announcing his resignation
from the Royal Bank of Canada. As Ronan later recalled the
moment, “The next ten messages said, ‘Holy shit, Brad Kat-
suyama just fucking resigned.’ ” Ronan knew that RBC’s bosses
up in Canada had been refusing, artfully, to deal with Brad’s
insistence that it would be better for all concerned if he not only
quit the bank to pursue an idea he had conceived whde working
for the bank but also took several of the bank’s most valuable
employees with him. The bosses in Canada clearly didn’t like
the sound of any part of this. They assumed that if they stalled
for time, Brad would come to his senses. What kind of Wall
Street trader quits a secure $2-million-plus-a-year job to start
a risky business — a business for which he doesn’t have even the
financial backing?
At baggage claim, Ronan reached Brad by phone. “I just
wanted to ask him: What the fuck is going on?’ ” Brad told him,
in surprisingly few words: He was tired of all these supposedly
important people who ran this supposedly important bank nod-
ding politely when he tried to speak to them about something
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155
that was far, far more important than any one person or any one
bank. “They were thinking he’d never do it,” said Ronan. “And
he was like, ‘Oh yeah, motherfucker?’ And he did it!” When
Ronan rang off, he thought: Well, he’s pushed me all in.
BRAD GOT TO work around 6:30 every morning. That first morn-
ing after the Christmas break, he went to his immediate superior
and told him that he was done. Then he went to his desk and
wrote one email to Ronan, Rob Park, and John Schwab, and
another to three senior guys in Canada. Five minutes later his
phone rang. It was Canada, outraged. What the hell are you doing?
asked the senior manager on the other end of the line. You can’t
do this. To which Brad said: I just did.
He left the bank with nothing — no paper, no code, no cer-
tainty that anyone would actually follow him out, and not even,
as it turned out, a clear idea for a business. Like everyone else
in the stock market, Brad had received a jolt when he read that
a Goldman Sachs high-frequency programmer had gone to
jail for mailing himself computer code. Goldman’s sensitivity
confirmed his suspicion that, around 2009, the big Wall Street
banks, previously distracted by the financial crisis, had finally
woken up to the value of the customer orders inside their own
dark pools. They were using fear and intimidation to control
the technologists who, ultimately, could exploit that value; and
the culture of finance suddenly was becoming more closed and
secretive — which was saying something. The people who now
did what Ronan had once done for the big banks and HFT
firms, for instance, would not be allowed to see and hear all
that Ronan had been allowed to see and hear. And the banks
were now using the legal system to make it harder for their
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more technical employees to leave. “I said to Rob, ‘No fucking
around,’ ” recalled Brad. “He said, ‘Don’t worry. There’s noth-
ing I’d want to take from here anyway.’ ”
They’d be starting fresh. They could use the insights about
the stock market gained from Thor, but Thor itself belonged
to the Royal Bank of Canada. Their main advantage — their
only sustainable advantage — was that investors trusted them.
The investors on the receiving end of Wall Street’s sales pitches
were not, by nature, trusting; or, if they were trusting by nature,
their natures were reshaped by their environment. People on
Wall Street were simply paid too much to lie and dissemble and
obfuscate, and so every trusting feeling in the financial markets
simply had to be followed by a trailing doubt. Something about
Brad had led investors to lower their guard and to trust him.
Whatever that was, it was sufficiently powerful that a group of
people who ran some of the world’s biggest mutual funds and
hedge funds, and who controlled roughly one third of the entire
United States stock market, petitioned his superiors at RBC,
after he had quit, to allow him to leave, so that he might restore
trust to the financial markets on a grander scale.
And yet — even as he walked away from millions of Wall
Street dollars — some of these very people raised questions about
his motives. He needed $10 million or so to hire the people who
could help him to design his new stock market, and to write the
computer code that would be the basis for that market. He’d
hoped — assumed, even — that these big investors would supply
him with the capital to build the new stock exchange, but eight
of every ten pitch meetings began with some version of the same
question: “Why are you doing this? Why are you attacking a
system that has made you rich and will make you even richer if
you just go along with it?” As one investor put it, behind Brad’s
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157
back, “I have a question about Brad: Have you figured out why
he’s playing Robin Hood?”
Brad’s first answer to that question was the thing he’d told
himself: The stock market had become grotesquely unjust, and
badly needed to be changed, and he’d come to see that, if he
didn’t do it, no one else would. “That didn’t sit well,” he recalled.
“They’d just say, ‘That sounds like complete bullshit.’ The first
couple of times it happened, it really bothered me.” Then he got
over it. If this new stock exchange flourished, its founders stood
to make money — maybe a lot of money. He wasn’t a monk; he
simply didn’t feel any need to make great sums of money. But
he noticed, weirdly, that when he stressed how much money
he himself might make from the new stock exchange, potential
investors in his new business warmed to him — and so he started
to stress how much money he might make. “We had a saying
that seemed to appease everyone when they asked why we are
doing this,” he said. “We are long-term greedy. That worked very
well. ... It always got a better response out of them than my
first answer.”
He spent six months running around New York faking greed
he didn’t really feel, to put money people at ease. It was mad-
dening: He couldn’t get the people who should give him money
to do so, and he couldn’t take the money from the people who
wanted to give it to him. Just about all of the big Wall Street
banks either asked him outright if they might buy a stake in his
exchange or wanted at least to be considered as possible inves-
tors. But if he took their money, his stock exchange would lose
both its independence and its credibility with investors. His
friends and family in Toronto also all wanted to invest in his
new company. They presented a different issue. Two hours after
Brad had let them know, via email, that he was pounding the
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pavement to raise money for a new stock market, they ponied
up, collectively, $1.5 million. Some of these people could afford
to take risks with their money, but some had no more than a few
thousand dollars in savings. Before he allowed them to invest,
Brad insisted that they send him bank statements to prove that
they could afford to lose whatever they invested. “Your brother
has never failed at anything he has ever done,” one old friend
wrote to Brad’s older brother, Craig, to explain why the new
business wasn’t at all risky, and to ask him to intercede on his
behalf and overrule Brad’s decision not to take his money.
What he needed was for the big stock market investors who
had said they wanted him to quit RBC to fix the stock market —
that is, the mutual funds, pension funds, and hedge funds — to
put their money where their mouth was. They offered all sorts
of excuses why they couldn’t help: They weren’t designed to
invest in start-ups; the investment managers thought it was a
great idea, but the compliance arm simply wasn’t equipped to
evaluate Brad; and so on. “The amount of money we were ask-
ing for was so small that it was too much of a pain in the ass
for them to figure out how to give it to us,” said Brad. They
all wanted him to build his exchange; they all hoped to benefit
from that exchange; but they all also assumed that someone else
would supply the capital to do it. Many had good excuses —
it was indeed outside the mission of a giant pension fund to
invest in start-ups. Still, it was disappointing. “They’re like one
of those fucking friends who say he’ll back you up in a fight and
they don’t do anything,” said Ronan, after one long and frustrat-
ing day of begging for capital. “You’re on the ground, bloody,
and only then do they jump in and throw a punch.”
Some of them were like that; but not all of them. The giant
mutual fund manager Capital Group pledged to invest — on the
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condition that they weren’t the lone investor but part of a con-
sortium; so did another, Brandes Investment Partners. And there
were several that voiced a sound objection: The business Brad
was pitching to them was a foggy proposition — a stock exchange
that existed mainly to route their stock market orders to all the
other exchanges. How would that work? Thor had worked great,
but why did Brad imagine that the predators who operated with
such abandon on America’s public and private exchanges would
not adapt to it? And why did he think Wall Street’s biggest banks
would subcontract the routing of their stock market orders to his
new exchange? Because it was “fair”? The banks’ salesmen ran
around every day selling the banks’ own routers. They weren’t
going to turn on a dime and say, “Oh yeah, we’ve been paid
huge sums of money to sell you out to high-frequency traders,
but now we’re going to give all the stock market orders to Brad,
so we can’t sell you out any longer.”
Brad didn’t fully understand the enterprise he needed to cre-
ate until the market forced him to, by not giving him the capital
for the enterprise he thought he wanted to create. Fuller under-
standing arrived in August 2012, in a meeting with David Ein-
horn, who ran the hedge fund Greenlight Capital. After listening
to Brad’s pitch, Einhorn asked him a simple question: Why aren’t
we all just picking the same exchange? Why didn’t investors organize
themselves to sponsor a single stock exchange entrusted with
guarding their interests and protecting them from Wall Street
predators? There’ d never been any collective pressure brought
by investors on the big banks to route their stock market orders
to any one exchange, but that was only because there was no
good reason to prefer one exchange over another: The fifty or so
places on which stocks were traded were all designed by finan-
cial intermediaries, for financial intermediaries. “It was so obvi-
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ous it was almost embarrassing,” said Brad. “That should have
been our pitch: not that we should route the orders using Thor
but [that] we should create the one place investors would choose
to go.” That is, they shouldn’t simply seek to defend investors
on the existing stock exchanges. They should seek to put all the
other exchanges out of business.
By mid-December he’d sewn up $9.4 million from nine dif-
ferent big money managers.* Six months later he’d raise $15 mil-
lion from four new investors. The money Brad needed that he
didn’t get he kicked in himself: By January 1, 2013, he’d put his
life savings on the line.
At the same time, he went looking for people: software devel-
opers and hardware engineers and network engineers to build
the system, the operations people to run it, and the salespeople
to explain it to Wall Street. He had no trouble attracting people
who knew him — -just the opposite. A shockingly large number
of people he’d worked with at RBC apparently felt the urge to
entrust him with their careers. Several dozen people had hinted
that they’d like to join him and do whatever he was doing. He
found himself in a series of bizarre conversations, in which he
tried to explain why they were better off being paid hundreds of
thousands of dollars a year to work at a big Wall Street bank than
taking a flier on a new business that had neither a clear plan nor
a penny of financing. Still, people followed. Allen Zhang, the
Golden Goose himself, got fired for sending RBC’s computer
code to himself and instantly turned up at Brad’s front door.
Billy Zhao was made redundant after he automated a compli-
* The first round of investors included Greenlight Capital, Capital Group, Brandes
Investment Partners, Senator Investment Group, Scoggin Capital Management, Belfer
Management, Pershing Square, and Third Point Partners.
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161
cated task so well that the bank no longer needed his help to do
it: He came on board, too. But Brad needed people who didn’t
know him, and who knew things he did not know. He needed,
especially, people with a deep understanding of high-frequency
trading and stock exchanges. And the first person he found was
Don Bollerman.
WHAT EVERYONE NOTICED about Don Bollerman — even if they
didn’t quite put it this way — was how badly he wanted not to be
surprised by his own life. On top of that, he’d grown up in the
Bronx and carried with him a resistance to sentiment. He ripped
the filters off cigarettes before he smoked them. He weighed
a hundred pounds more than he should and ignored entreat-
ies from his colleagues to exercise or take care of himself. “I’m
gonna die young anyway,” he’d say. His finer feelings he treated
much the way he treated his body, with something approaching
disdain. “Much is made of a kind heart,” he said. “I’m more of a
feed-yourself-or-die kind of guy.”
To eliminate the possibility of surprise required not that
Don’s life be especially unsurprising but that he control his feel-
ings about whatever surprise it produced. How much he wished
to manage these emotions could be seen when they were at
their least manageable. On September 11, 2001, Don worked
at a small new electronic stock exchange on the twelfth floor
of 100 Broadway, five hundred yards from the World Trade
Center. He’d arrived at seven that morning. Before the stock
market opened, he heard a bump, which sounded as if it had
come from upstairs. “What we thought is that it was guys mov-
ing heavy equipment,” he said. “Five minutes later it’s snowing
office memos.” He and his colleagues went to the window and
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heard the news on the office TV about the plane hitting one
of the towers. “I thought it was an attack right away,” he said,
and so he was less shocked than his colleagues by what hap-
pened next. They had a direct view of the Twin Towers, across
the Trinity Church graveyard, over the top of the American
Stock Exchange. The second plane hit. “I felt the heat on my
face through the window. You open the barbecue and your face
feels like it pulls back — that feeling,” he said. They discussed
whether the towers were tall enough to reach them if one fell
over. Then the first tower fell. “That’s when we ran for the
staircase.” By the time they got to the sixth floor, Don couldn’t
see his hands in front of his face. Once outside, in the blizzard,
he headed east. He walked alone and matter-of-factly up Third
Avenue and then across the bridge over the Harlem River to his
apartment in the Bronx, sixteen miles in all. What stuck out in
his mind from the day was how, when he arrived in Harlem,
some women were waiting outside their homes with fruit juice
for him to drink. “That one caught in my throat,” he said. He
added quickly, “Actually, I feel like a bit of a pussy, that it got to
me that way.”
The attack, and the ensuing market convulsions, killed off
the new electronic stock exchange that employed him. Don,
who had thought that the business was probably going to die
anyway, went back to NYU to finish his college degree, and
then on to a career at the Nasdaq stock exchange. Seven years
in, his job was to deal with everything that happened after a
trade occurred, but his specific role was less important than
his general understanding — both Ronan and Schwab thought
that Don Bollerman knew breathtakingly more about the inner
workings of the stock exchanges than anyone they had ever met.
He’d been privy to just about everything that happened inside
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Nasdaq, and brought an understanding not just of what had
gone wrong but how it might be set right.
What had gone wrong, in Don’s view, wasn’t all that surpris-
ing or complicated. It had to do with human nature, and the
power of incentives. The rise of high-frequency trading — and
its ability to gain an edge on the rest of the market — had cre-
ated an opportunity for new exchanges, like BATS and Direct
Edge. By giving HFT what it wanted (speed, in relation to the
rest of the market; complexity only HFT understood; and pay-
ment to brokers for their customers’ orders, so that HFT had
something to trade against), the new stock exchanges had stolen
market share from the old stock exchanges. Don couldn’t speak
for NYSE, but he had watched Nasdaq respond by giving HFT
firms what they asked for — and then figuring out how to charge
them for it. “It was almost like you couldn’t do anything about
it,” he said. “We did all this speed, and I don’t think we fully
understood what it was being used for. We just thought, The
new rules caused people to have a new experience and then
new wants and needs.” Nasdaq had become a public company in
2005, a year after Don had joined it. It had earnings targets to
hit; it was incentivized to make decisions, and to make changes
in the nature of the exchange, with a focus on their short-term
consequences. “It’s hard to be forward-thinking when the whole
of corporate America is about the next quarter’s earnings,” said
Don. “It went from ‘Is this good for the market?’ to ‘Is this bad
for the market?’ And then it slides to: ‘Can we get this through
the SEC?’ The demon in this part of the story is expediency.”
By late 2011, when Bollerman quit his job (“I felt there was a
lack of leadership”), more than two-thirds of Nasdaq’s revenues
derived, one way or another, from high-frequency trading firms.
Don wasn’t shocked or even all that disturbed by what had
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happened, or, if he was, he disguised his feelings. The facts of
Wall Street life were inherently brutal, in his view. There was
nothing that he couldn’t imagine someone on Wall Street doing.
He was fully aware that the high-lrequency traders were prey-
ing on investors, and that the exchanges and brokers were being
paid to help them to do it. He refused to feel morally outraged
or self-righteous about any of it. “I would ask the question, ‘On
the savannah, are the hyenas and the vultures the bad guys?’ ” he
said. “We have a boom in carcasses on the savannah. So what?
It’s not their fault. The opportunity is there.” To Don’s way
of thinking, you were never going to change human nature —
though you might alter the environment in which it expressed
itself. Or maybe that’s just what Don wanted to believe. “He’s
kind of like the mob guy who cries every now and then after a
hit,” said Brad, who thought that Don was exactly the sort of
person he needed. Brad wasn’t in the market for self-righteous-
ness, or for people who defined themselves by their fine moral
sentiment. “Disillusion isn’t a useful emotion,” he said. “I need
soldiers.” Don was a soldier.
THEIR NEW EXCHANGE needed a name. They called it the Investors
Exchange, which wound up being shortened to IEX.* Its goal
was not to exterminate the hyenas and the vultures but, more
subtly, to eliminate the opportunity for the kill. To do that,
they needed to figure out the ways that the financial ecosystem
favored predators over their prey. Enter the Puzzle Masters.
* In the interest of clarity, they d hoped to preserve the full name, but they discovered
a problem doing so when they set out to create an Internet address: investorsexchange.
com. To avoid that confusion, they created another.
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Back in 2008, when it had first occurred to Brad that the stock
market had become a black box whose inner workings eluded
ordinary human understanding, he’d gone looking for techno-
logically gifted people who might help him open the box and
understand its contents. He’d started with Rob Park; with less
precision, he gathered others. One was a twenty-year-old Stan-
ford junior named Dan Aisen, whose resume Brad discovered in
a pile at RBC. The line that leapt out at him was “Winner of
the Microsoft College Puzzle Challenge.” Every year, Microsoft
sponsored this one-day, ten-hour national brain-twisting mara-
thon. It attracted thousands of young math and computer science
types. Aisen and three friends had competed, in 2007, against
one thousand other teams and had won the whole thing. “It’s
kind of a mix of cryptography, ciphers, and Sudoku,” explained
Aisen. The solution to each puzzle offered clues to the other
puzzles; to be really good at it, a person needed not only tech-
nical skill but exceptional pattern recognition. “There’s some
element of mechanical work, and some element of ‘aha!’” said
Aisen. Brad had given Aisen both a job and a nickname, the
Puzzle Master, soon shortened, by RBC’s traders, to Puz. Puz
was one of the people who had helped him create Thor.
Puz’s peculiar ability to solve puzzles was suddenly even more
relevant. Creating a new stock exchange is a bit like creating
a casino: Its creator needs to ensure that the casino cannot in
some way be exploitable by the patrons. Or, at worst, he needs
to know exactly how his system might be exploited, so that
he might monitor the exploitation — as a casino monitors card
counting at the blackjack tables. “You are designing a system,”
said Puz, “and you don’t want the system to be gameable.” The
trouble with the stock market — with all of the public and private
exchanges — was that they were fantastically gameable, and had
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been gamed: first by clever guys in small shops and then by prop
traders at the big Wall Street banks. That was the problem, Puz
thought. From the point of view of the most sophisticated trad-
ers, the stock market wasn’t a mechanism for channeling capital
to productive enterprise but a puzzle to be solved. “Investing
shouldn’t be about gaming a system,” he said. “It should be
about something else.”
The simplest way to design a stock exchange that could not
be gamed was to hire the very people best able to game it, and
encourage them to take their best shots. Brad didn’t know any
other national puzzle champions, but Puz did. The first per-
son he mentioned was his former Stanford teammate Francis
Chung. Francis worked as a trader at a high-frequency trading
firm but didn’t like his job. Brad invited him in for a job inter-
view. Francis turned up — and just sat there.
Brad gazed across a table: The young man was round-faced
and shy and sweet-natured but essentially noninteractive.
“Why are you good at solving puzzles?” Brad asked him.
Francis thought about it a moment.
“I’m not sure how good I am,” said Francis.
“You just won the national puzzle-solving championship!”
Francis thought about that some more.
“Yeah, I guess,” he said.
Brad had done a lot of these interviews with technologists
whose skills he could not judge. He left it to Rob to figure out
if they could actually write code. He just wanted to know what
kind of people they were. “I’m just looking for the type of peo-
ple who won’t get along here,” said Brad. “Typically, it’s because
the way they describe their experience, and the things they say,
are very self-serving. ‘I don’t get enough credit for what I do,’ or
I’m overlooked.’ It’s all about me. They’re obsessed with titles
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167
and other things that don’t matter. I try to find out how they
work with other people. If they don’t know something, what do
they do? I look for sponges, learners.” With Francis he had no
idea. Every question elicited some choked reply. Desperate to get
something, anything, out of him, Brad finally asked, “All right,
just tell me: What do you like to do?” Francis thought about it.
“I like to dance,” he said. Then he went completely silent.
After Francis had left, Brad hunted down Puz. “Are you sure
this is the guy?” he asked.
“Trust me,” said Puz.
It took roughly six weeks for Francis to get comfortable
enough to speak up. Once he did, he wouldn’t shut up. It was
Francis who would eventually take all the rules they created for
the exchange and translate them into step-by-step instructions
for a computer to follow. Francis alone had the entire logic of
the new exchange in his head. Francis fought more than anyone
for, as he put it, “making the system so simple there is nothing
to game.” And it was Francis whom Bollerman dubbed The
Spoiler, because every time the other guys thought they had
figured something out, Francis would step in and show them
some loophole in their logic. “The level to which the kid will
worry a problem is what really separates him,” said Don Boiler-
man, “without any prior concern for whose theory he’s going to
upset — including his own.”
The only problem with the Puzzle Masters was that neither
of them had ever worked inside a stock exchange. Bollerman
brought in a guy from Nasdaq, Constantine Sokoloff, who had
helped to build the exchange’s matching engine. “The Puzzle
Masters needed a guide, and Constantine was that guide,” said
Brad. Constantine was also Russian, born and raised in a small
town on the Volga River. He had a theory about why so many
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Russians had wound up inside high-frequency trading. The
old Soviet educational system channeled people away from the
humanities and into math and science. The old Soviet culture
also left its former citizens oddly prepared for Wall Street in
the early twenty-first century. The Soviet-controlled economy
was horrible and complicated but riddled with loopholes. Every-
thing was scarce; everything was also gettable, if you knew how
to get it. “We had this system for seventy years,” said Constan-
tine. “People learn to work around the system. The more you
cultivate a class of people who know how to work around the
system, the more people you will have who know how to do it
well. All of the Soviet Union for seventy years were people who
are skilled at working around the system.” The population was
thus well suited to exploit megatrends in both computers and the
United States financial markets. After the fall of the Berlin Wall,
a lot of Russians fled to the United States without a lot of Eng-
lish; one way to make a living without having to converse with
the locals was to program their computers. “1 know people who
never programmed computers but when they get here they say
they are computer programmers,” said Constantine. A Russian
also tended to be quicker than most to see holes built into the
U.S. stock exchanges, even if those holes were unintentional,
because he had been raised by parents, in turn raised by their
own parents, to game a flawed system.
The role of the Puzzle Masters was to ensure that the new
stock exchange did not contain aspects of a puzzle. That it had
no problem inside its gears that could be “solved.” To begin, they
listed the features of the existing stock exchanges and picked
them apart. Aspects of the existing stock exchanges obviously
incentivized bad behavior. Rebates, for instance: The maker-
taker system of fees and kickbacks used by all of the exchanges
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169
was simply a method for paying the big Wall Street banks to
screw the investors whose interests they were meant to guard.
The rebates were the bait in the high-frequency traders’ flash
traps. The moving parts of the traps were order types. Order
types — like “market” and “limit” — exist so that the person
who submits the order to buy or sell stock retains some control
over his order after it has entered the marketplace.* They are an
acknowledgment that the investor cannot be physically present
on the exchange to micromanage his situation. Order types also
exist, less obviously, so that the person who is buying or selling
stock can embed, in a single simple instruction, a lot of other,
smaller instructions.
The old order types were simple and straightforward and mainly
sensible. The new order types that accompanied the explosion of
high-frequency trading were nothing like them, either in detail
or spirit. When, in the summer of 2012, the Puzzle Masters gath-
ered with Brad and Don and Ronan and Rob and Schwall in a
room to think about them, there were maybe one hundred fifty
* The market order is the first and simplest type. Say, for instance, an investor wishes to
buy 100 shares of Procter & Gamble. When he submits his order, the market for the shares
in P&G is, say, 80-80.02. If he submits a market order, he will pay the offering price — in
this case, $80.02 per share. But a market order comes with a risk: that the market will
move between the time the order is submitted and the time it reaches the market. The
flash crash was a dramatic illustration of that risk: Investors who submitted market orders
wound up paying $100,000 a share for P&G and selling those same shares for a penny
apiece. To control the risk of a market order, a second order type was invented, the limit
order. The buyer of P&G shares might say, for instance: “I’ll buy a hundred shares, with
a limit of eighty dollars and three cents a share.” By doing so, he will ensure that he does
not pay $100,000 a share; but this may lead to a missed opportunity — he may not buy the
shares at all, because he never gets the price he wanted. Another simple, and long-used,
order type is “good ’til canceled.” The investor who says he wants to buy 100 shares of
P&G at $80 a share, “good ’til canceled,” will never have to think about it again until
he buys them, or does not.
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different order types. What purpose did each serve? How might
each be used? The New York Stock Exchange had created an order
type that ensured that the trader who used it would trade only if
the order on the other side of his was smaller than his own order;
the purpose seemed to be to prevent a high-frequency trader from
buying a small number of shares from an investor who was about
to crush the market with a huge sale. Direct Edge created an
order type that, for even more complicated reasons, allowed the
high-frequency trading firm to withdraw 50 percent of its order
the instant someone tried to act on it. All of the exchanges offered
something called a Post-Only order. A Post-Only order to buy
100 shares of Procter & Gamble at $80 a share says, “I want to buy
a hundred shares of Procter & Gamble at eighty dollars a share,
but only if I am on the passive side of the trade, where I can collect
a rebate from the exchange.” As if that weren’t squirrely enough,
the Post-Only order type now had many even more dubious per-
mutations. The Hide Not Slide order, for instance. With a Hide
Not Slide order, a high-frequency trader — for who else could or
would use such a thing? — would say, for example, “I want to buy
a hundred shares of P&G at a limit of eighty dollars and three
cents a share, Post-Only, Hide Not Slide.”
One of the joys of the Puzzle Masters was their ability to
figure out what on earth that meant. The descriptions of single
order types filed with the SEC often went on for twenty pages,
and were in themselves puzzles — written in a language barely
resembling English and seemingly designed to bewilder anyone
who dared to read them. “I considered myself a somewhat expert
on market structure,” said Brad. “But I needed a Puzzle Master
with me to fully understand what the fuck any of it means.”
A Hide Not Slide order — it was just one of maybe fifty such
problems the Puzzle Masters solved — worked as follows: The
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171
trader said he was willing to buy the shares at a price ($80.03)
above the current offering price ($80.02), but only if he was on
the passive side of the trade, where he would be paid a rebate.
He did this not because he wanted to buy the shares. He did
this in case an actual buyer of stock — a real investor, channeling
capital to productive enterprise — came along and bought all
the shares offered at $80.02. The high-frequency trader’s Hide
Not Slide order then established him as first in line to purchase
P&G shares if a subsequent investor came into the market to
sell those shares. This was the case even if the investor who
had bought the shares at $80.02 expressed further demand for
them at the higher price. A Hide Not Slide order was a way for
a high-frequency trader to cut in line, ahead of the people who’d
created the line in the first place, and take the kickbacks paid to
whoever happened to be at the front of the line.
The Puzzle Masters spent days working through the many
order types. All of them had one thing in common: They were
designed to create an edge for HFT at the expense of investors.
“We’d always ask, ‘What is the point of that order, if you want
to trade?’ ” said Brad. “Most of the order types were designed to
not trade, or at least to discourage trading. [With] every rock we
turned over, we found a disadvantage for the person who was
actually there to trade.” Their purpose was to hardwire into the
exchange’s brain the interests of high-frequency traders — at the
expense of everyone who wasn’t a high-frequency trader. And
the high-frequency traders wanted to obtain information, as
cheaply and risklessly as possible, about the behavior and inten-
tions of stock market investors. That is why, though they made
only half of all trades in the U.S. stock market, they submitted
more than 99 percent of the orders: Their orders were a tool
for divining information about ordinary investors. “The Puzzle
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Masters showed me the length the exchanges were willing to go
to — to satisfy a goal that wasn’t theirs,” said Brad.
The Puzzle Masters might not have thought of it this way at
first, but in trying to design their exchange so that investors who
came to it would remain safe from high-frequency traders, they
were also divining the ways in which high-frequency traders
stalked their prey. As they worked through the order types, they
created a taxonomy of predatory behavior in the stock market.
Broadly speaking, it appeared as if there were three activities
that led to a vast amount of grotesquely unfair trading. The first
they called “electronic front-running” — seeing an investor try-
ing to do something in one place and racing him to the next.
(What had happened to Brad, when he traded at RBC.) The
second they called “rebate arbitrage” — using the new complexity
to game the seizing of whatever kickbacks the exchange offered
without actually providing the liquidity that the kickback was
presumably meant to entice. The third, and probably by far
the most widespread, they called “slow market arbitrage.” This
occurred when a high-frequency trader was able to see the price
of a stock change on one exchange, and pick off orders sitting on
other exchanges, before the exchanges were able to react. Say, for
instance, the market for P&G shares is 80-80.01, and buyers and
sellers sit on both sides on all of the exchanges. A big seller comes
in on the NYSE and knocks the price down to 79.98—79.99.
High-frequency traders buy on NYSE at $79.99 and sell on all
the other exchanges at $80, before the market officially changes.
This happened all day, every day, and generated more billions of
dollars a year than the other strategies combined.
All three predatory strategies depended on speed, and to
speed the Puzzle Masters turned their attention, once they were
done with the order types. They were trying to create a safe
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173
place, where every dollar stood the same chance. How to do
that, when a handful of people in the market would always be
faster than everyone else? They couldn’t very well prohibit high-
frequency traders from trading on the exchange— an exchange
needed to offer fair access to all broker-dealers. And, anyway, it
wasn’t high-frequency trading in itself that was pernicious; it was
its predations. It wasn’t necessary to eliminate high-frequency
traders; all that was needed was to eliminate the unfair advan-
tages they had, gained by speed and complexity. Rob Park put it
best: “Let’s say you know something before everyone else. You
are in a privileged state. Eliminating the position of privilege is
impossible — some people always will get the information first.
Some people will always get it last. You can’t stop it. What you
can control is how many moves they can make to monetize it.”
The obvious starting point was to prohibit high-frequency
traders from doing what they had done on all the other
exchanges — co-locating inside them, and getting the informa-
tion about whatever happened on those exchanges before every-
one else.* That helped, but it did not entirely solve the problem:
High-frequency traders would always be faster at processing the
information they acquired from any exchange, and they would
always be faster than anyone else to exploit that information on
* The value of the microseconds saved by proximity to the exchanges explained why the
exchanges expanded, bizarrely, after the people inside them had vanished. You might
have thought that, when the whole of the stock market moved from a floor that needed
to accommodate thousands of human traders into a single black box, the building that
housed the exchange might shrink. Think again. The old New York Stock Exchange
building on the corner of Wall and Broad streets was 46,000 square feet. The NYSE
data center in Mahwah, which housed the exchange, was 400,000 square feet. Because
the value of the space around the black box was so great, the exchanges expanded to
enclose greater amounts of that space so that they might sell it. IEX could function hap-
pily inside a space roughly the size of a playhouse.
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other exchanges. This new exchange would be required both
to execute trades on itself and to route, to the other exchanges,
the orders it was unable to execute. The Puzzle Masters wanted
to encourage big orders, and larger-sized trades, so that honest
investors with a lot of stock to sell might collide with honest
investors who had a lot of stock to buy, without the intercession
of HFT. If some big pension fund came to IEX to buy a million
shares of P&G and found only 100,000 for sale there, it would
be exposed to some high-frequency trader figuring out that its
demand for P&G shares was unsatisfied. The Puzzle Masters
wanted to be sure that they could beat any HFT firm to the sup-
ply of P&G stock on the other exchanges.
They entertained all sorts of ideas about how to solve the
speed problem. “We had professors coming through here con-
stantly,” said Brad. For instance, one professor suggested a
“randomized delay.” Every order submitted to the new stock
exchange would be assigned, at random, some time lag before
it entered the market. The market information some high-fre-
quency trader obtained with his 100-share sell order, the sole
intention of which was to uncover the existence of a big buyer,
might thus move so slowly that it would prove of no use to him.
An order would become, like a lottery ticket, a matter of chance.
The Puzzle Masters instantly spotted the problem: Any decent
HFT firm would simply buy huge numbers of lottery tickets —
to increase its chances of being the 100-share sell order that
collided with the massive buy order. “Someone will just flood
the market with orders,” said Francis. “You end up massively
increasing quote traffic for every move.”
It was Brad who had the crude first idea: Everyone is fighting
to get in as close to the exchange as possible. Why not push them as far
away as possible? Put ourselves at a distance, but don’t let anyone else be
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there. In designing the exchange, they needed to consider what
the regulators would tolerate; they couldn’t just do whatever they
wanted. Brad kept a close eye on what the regulators already had
approved, and paid special attention when the New York Stock
Exchange won the SEC’s approval for the strange thing they
had done in Mahwah. They’d built this 400,000-square-foot
fortress in the middle of nowhere, and they planned to sell, to
high-frequency traders, access to their matching engine. But
the moment they announced their plans, high-frequency trad-
ing firms began to buy up land surrounding the fort — so that
they might be near the NYSE matching engine, without paying
the NYSE for the privilege. In response, the NYSE somehow
persuaded the SEC to let them make a rule for themselves: Any
banks or brokers or HFT firms that did not buy (expensive)
space inside the fort would be allowed to connect to the NYSE
in one of two places: Newark, New Jersey, or Manhattan. The
time required to move a signal from those places to Mahwah
undermined EIFT strategies; and so the banks and brokers and
HFT firms were all forced to buy space inside the fort from
the NYSE. Brad thought: Why not create the distance that under-
mines HFT’s strategies, without selling high-frequency traders the right
to put their computers in the same building? “There was a precedent:
They’d let NYSE do it,” Brad said. “Unless the regulators said,
‘You must allow co-location,’ ” they’d have to let IEX forbid it.
The idea was to establish the IEX computer that matched
buyers and sellers (the matching engine) at some meaningful
distance from the place traders connected to IEX (called the
“point of presence”), and to require anyone who wanted to
trade to connect to the exchange at that point of presence. If
you placed every participant in the market far enough away
from the exchange, you could eliminate most, and maybe all,
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of the advantages created by speed. Their matching engine,
they already knew, would be located in Weehawken, New Jer-
sey (they’d been offered cheap space in a data center). The only
question was: Where to put the point of presence? “Let’s put
it in Nebraska,” someone said, but they all knew it would be
harder to get the already reluctant Wall Street banks to connect
to their market if the banks had to send people to Omaha to do
it. Actually, though, it wasn’t necessary for anyone to move to
Nebraska. The delay needed only to be long enough for IEX,
once it had executed some part of a customer’s buy order, to beat
HFT in a race to any other shares available in the marketplace at
the same price — that is, to prevent electronic front-running. It
needed to be long enough, also, for IEX, each time a share price
moved on any exchange, to process the change, and to move the
prices of any orders resting on it, so that they didn’t get picked
off — in the way, say, that Rich Gates had been picked off, when
he ran his tests to determine if he was being ripped off inside the
dark pools run by the big Wall Street banks. (That is, to prevent
“slow market arbitrage.”) The necessary delay turned out to be
320 microseconds; that was the time it took them, in the worst
case, to send a signal to the exchange farthest from them, the
NYSE in Mahwah. Just to be sure, they rounded it up to 350
microseconds.
The new stock exchange also cut off the food source for all
identifiable predators. Brad, when he was a trader, had been
cheated because his orders had arrived first at BATS, where
HFT guys had picked up his signal and raced him to the other
exchanges. The fiber routes through New Jersey that Ronan
handpicked were chosen so that an order sent from IEX to the
other exchanges arrived at them all at precisely the same time.
(He thus achieved with hardware what Thor had achieved with
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177
software.) Rich Gates had gotten himself picked off in the Wall
Street dark pools because the dark pools had not moved fast
enough to re-price his order. The slow movement of the dark
pools’ prices had made it possible for a high-frequency trader (or
the Wall Street banks’ own traders) to exploit the orders inside
it — legally. To prevent the same thing from happening on their
new exchange, IEX needed to be extremely fast — much faster
than any other exchange. (At the same time that they were slow-
ing down everyone who traded on their exchange, they were
speeding themselves up.) To “see” the prices on the other stock
exchanges, IEX didn’t use the SIP or some phony improvement
on the SIP but instead created their own private, HFT-like pic-
tures of the entire stock market. Ronan had scoured New Jersey
for paths from their computers in Weehawken to all the other
exchanges; there turned out to be thousands of them. “We used
the fastest subterranean routes,” said Ronan. “All the fiber we
used was created by EIFT for HFT. One hundred percent of it.”
The 350-microsecond delay worked like a head start in a foot-
race. It ensured that IEX would be faster to see and react to the
wider market than even the fastest high-frequency trader, thus
preventing investors’ orders from being abused by changes in that
market. In the bargain, it prevented high-frequency traders —
who would inevitably try to put their computers nearer than
everyone else’s to IEX’s in Weehawken — from submitting their
orders onto IEX more quickly than everyone else.
To create the 350-microsecond delay, they needed to keep
the new exchange roughly thirty-eight miles from the place the
brokers were allowed to connect to the exchange. That was a
problem. Having cut one very good deal to put the exchange in
Weehawken, they were offered another: to establish the point of
presence in a data center in Secaucus, New Jersey. The two data
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centers were less than ten miles apart, and already populated
by other stock exchanges and all the high-frequency traders.
(“Were going into the lion’s den,” said Ronan.) A bright idea
came from a new employee, James Cape, who had just joined
them from an HFT firm: Coil the fiber. Instead ot running straight
fiber between the two places, coil thirty-eight miles of fiber
and stick it in a compartment the size of a shoebox to simulate
the effects of the distance. And that’s what they did. The infor-
mation flowing between IEX and all the players on it would
thus go round and round, in thousands of tiny circles, inside the
magic shoebox. From the high-frequency traders’ point of view,
it was as if they’d been banished to West Babylon, New York.
Creating fairness was remarkably simple. They would not sell
to any one trader or investor the right to put his computers next
to the exchange, or special access to data from the exchange.
They would pay no kickbacks to brokers or banks that sent orders;
instead, they’d charge both sides of any trade the same amount:
nine one-hundredths of a cent per share (known as 9 “mils”).
They’d allow just three order types: market, limit, and Mid- Point
Peg, which meant that the investor’s order rested in between the
current bid and offer of any stock. If the shares of Procter & Gam-
ble were quoted in the wider market at 80-80.02 (you can buy at
$80.02 or sell at $80), a Mid-Point Peg order would trade only at
$80.01. “It’s kind of like the fair price,” said Brad.
Finally, to ensure that their own incentives remained as closely
aligned as they could be with those of stock market investors, the
new exchange did not allow anyone who could trade directly on
it to own any piece of it: Its owners were all ordinary investors
who needed first to hand their orders to brokers.
The design of the new stock exchange was such that it would
yield all sorts of new information about the inner workings of
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179
the U.S. stock market — and, indeed, the entire financial system.
For instance, it did not ban but welcomed high-frequency trad-
ers who wished to trade on it. It high-frequency traders per-
formed a valuable service in the financial markets, they should
still do so, after their unfair advantages had been eliminated.
Once the new stock exchange opened for business, IEX would
be able to see how much of what HFT did was useful simply by
watching what, it anything, high-frequency traders did on the
new exchange, where predation was not possible. The Puzzle
Masters’ only question was whether, in their design, they had
accounted for every possible form of market predation. That was
the one thing even they did not know: whether they had missed
something.
THE HIDDEN PASSAGES and trapdoors that riddled the exchanges
enabled a handlul ot players to exploit everyone else; the latter
didn’t understand that the game had been designed precisely for
the former. As Brad put it, “It’s like you run this casino, and you
need to get players in to attract other players. You invite a few
players in to start a game of Texas Flold’em by telling them that
the deck doesn’t have any jacks or queens in it, and that you won’t
tell the other people who come to play with them. Flow do you
get people into the casino? You pay the brokers to bring them
there.” By the summer of 2013, the world’s financial markets
were designed to maximize the number of collisions between
ordinary investors and high-frequency traders — at the expense
of ordinary investors, and for the benef it of high-frequency trad-
ers, exchanges, Wall Street banks, and online brokerage firms.
Around those collisions an entire ecosystem had arisen.
Brad had heard many firsthand accounts about the nature
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of that ecosystem. One came from a man named Chris Nagy,
who, until 2012, had been responsible for selling the order flow
for TD Ameritrade. Every year, people from banks and high-
frequency trading firms would fly to Omaha, where TD Ameri-
trade was based, and negotiate with Nagy. “Most of the deals
tend to be handshake deals,” Nagy said. “You go out to a steak
dinner. ‘We’ll pay you two cents a share. Everything is good.’”
The negotiations were always done face-to-face, because no one
involved wanted to leave a paper trail. “The payment for the
order flow is as off-the-record as possible,” said Nagy. “They
never have an email or even a phone call. You had to fly down
to meet with us.” For its part, TD Ameritrade was required to
publish how much per share they were making from the prac-
tice but not the total amounts, which were buried on its income
statements on a line labeled “Other Revenue.” “So you can see
the income, but you can’t see the deals.”
In his years selling order flow, Nagy noticed a couple of
things — and he related them both to Brad and his team when
he came to visit them to find out why he kept hearing about
this strange new thing called IEX. The first was that the mar-
ket complexity created by Reg NMS — the rapid growth in the
number of stock markets, and in high-frequency trading — raised
the value of a stock market customer’s order. “It caused the value
of our flow to triple, a least,” Nagy said. The other thing he
couldn’t help but notice was that not all of the online brokers
appreciated the value of what they were selling. TD Ameri-
trade was able to sell the right to execute its customers’ orders
to high-frequency trading firms for hundreds of millions a year.
The bigger Charles Schwab, whose order flow was even more
valuable than TD Ameritrade’s, had sold its flow to UBS back
in 2005, in an eight-year deal, for only $285 million. (UBS
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181
charged the high-frequency trading firm Citadel some undis-
closed sum to execute Schwab’s trades.) “Schwab left at least a
billion dollars on the table,” Nagy said. A lot of the people sell-
ing their customers’ orders, it seemed to Nagy, had no idea of
the value of the information the orders contained. Even he was
unsure; the only way to know would be to find out how much
money high-frequency traders were making by trading against
slow-footed individual investors. “I’ve tried over the years [to
find out how much money was being made by high-frequency
trading],” Nagy said. “The market makers are always reluctant
to share their performance.” What Nagy did know was that the
simple retail stock market order was, from the point of view of
high-frequency traders, easy kill. “Whose order flow is the most
valuable?” he said. “Yours and mine. We don’t have black boxes.
We don’t have algos. Our quotes are late to the market — a full
second behind.”*
High-frequency traders sought to trade as often as possible
with ordinary investors, who had slower connections. They
were able to do so because the investors themselves had only the
faintest clue of what was happening to them, and also because
the investors, even big, sophisticated ones, had no ability to con-
trol their own orders. When, say, Fidelity Investments sent a big
stock market order to Bank of America, Bank of America treated
that order as its own — and behaved as if it, not Fidelity, owned
the information associated with that order. The same was true
* In 2008, Citadel bought a stake in the online broker E*Trade, which was flounder-
ing in the credit crisis. The deal stipulated that E*Trade route some percentage of its
customers’ orders to Citadel. At the same time, E*Trade created its own high-frequency
trading division, eventually called G1 Execution Services, to exploit the value of those
orders for itself. Citadel’s founder and CEO, Kenneth Griffin, pitched a fit, and called
out E*Trade publicly for failing to execute its customers’ orders properly.
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when an individual investor bought stock through an online
broker. The moment he pressed the Buy icon on his screen, the
business was out of his hands, and the information about his
intentions belonged, in effect, to E*Trade, or TD Ameritrade
or Schwab.
But the role in this of the nine big Wall Street banks that
controlled 70 percent of all stock market orders was more com-
plicated than the role played by TD Ameritrade. The Wall Street
banks controlled not only the orders, and the informational value
of those orders, but dark pools in which those orders might be
executed. The banks took different approaches to milking the
value of their customers’ orders. All of them tended to send the
orders first to their own dark pools before routing them out to
the wider market. Inside the dark pool, the bank could trade
against the orders themselves; or they could sell special access to
the dark pool to high-frequency traders. Either way, the value
of the customers’ orders was monetized — by the big Wall Street
bank, for the big Wall Street bank. If the bank was unable to
execute a stock market order in its own dark pool, the bank
directed that order first to the exchange that paid the biggest
kickback for it — when the kickback was simply the bait for some
flash trap.
It the Puzzle Masters were right, and the design of IEX elimi-
nated the advantage of speed, IEX would reduce the value of
investors’ stock market orders to zero. If the orders couldn’t be
exploited on this new exchange — if the information they con-
tained was worthless — who would pay for the right to execute
them? The big Wall Street banks and online brokers charged by
investors with routing stock market orders to IEX would sur-
render billions of dollars in revenues in the process. And that, as
everyone involved understood, wouldn’t happen without a fight.
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183
One afternoon during the summer of 2013, a few months
before the exchange planned to open for business, Brad called
a meeting to figure out how to make the big Wall Street banks
feel watched. IEX had raised more capital and hired more peo-
ple and moved to a bigger room, on the thirtieth floor of 7
World Trade Center. There still was no separate place to meet,
however, so they gathered in a corner of the big room, where a
whiteboard met a window that offered a spectacular view of the
9/11 memorial. Don leaned with his back against the window,
along with Ronan, Schwall, and Rob Park, while Brad stood in
front of the whiteboard and took a whiteboard marker out of a
bin. The twenty or so other employees of IEX remained at their
desks in the room, pretending that nothing was happening.
Then Matt Trudeau appeared and joined in. Matt was the
only person in the room who had ever opened a brand-new
stock exchange, and so he tended to be included in every busi-
ness discussion. Oddly enough, among them he was least, by
nature, a businessman. He’d entered college to major in painting
and then, deciding he lacked the talent to make it as a painter,
and thinking he might make it as an academic, had moved into
the anthropology department. He didn’t become an anthropolo-
gist, either. Atter college he’d found work adjusting auto insur-
ance claims — a job he judged to be among the world’s most
soul-sucking. One day on a lunch break, he noticed a televi-
sion switched on to CNBC and wondered, “Why are there two
separate ticker tapes?” He began to study the stock market. Five
years later, in the mid-2000s, he was opening new, American-
style stock exchanges in foreign countries for a company with the
mystifying name Chi-X Global. (“It was marketing gone awry,”
he said. “We spent the first fifteen minutes of every meeting try-
ing to explain our name.”) He’d been one part businessman and
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one part missionary: He met with officials of various govern-
ments, wrote white papers, and sat on panels to extol the virtues
of American financial markets. After opening Chi-X Canada,
he’d advised firms trying to open stock exchanges in Singapore,
Tokyo, Australia, Hong Kong, and London. “Did I think I was
doing God’s work?” he said later. “No. But I did think market
efficiency was something important for the economy.”
As he spread the American financial gospel, he couldn’t help
but notice a pattern: A new exchange would open, and nothing
would happen on it — until the high-frequency traders showed
up, stuck their computers beside the exchange’s matching
engine, and turned the exchange around. Then he began to hear
things — that some of the HFT guys might be shady, that stock
exchanges had glitches built into them that HFT could use to
exploit ordinary investors. He couldn’t point to specific wrong-
doing, but he felt less and less easy about his role in the universe.
In 2010, Chi-X promoted him to a big new job. Global Head of
Product; but before he took the job he came across an Internet
post by Sal Arnuk and Joseph Saluzzi.* The post showed, in
fine detail, how data about investors’ orders provided to high-
frequency traders by two of the public exchanges, BATS and
Nasdaq, helped HFT discern investors’ trading intentions. Most
investors, Arnuk and Saluzzi wrote, “have no idea that the pri-
vate trade information they are entrusting to the market centers
is being made public by the exchanges. The exchanges are not
making this clear to their clients, but instead are actively broad-
* Arnuk and Saluzzi, the principals of Themis Trading, have done more than anyone to
explain and publicize the predation in the new stock market. They deserve more lines
in this book than they receive but have written their own book on the subject, Broken
Markets.
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185
casting the information to the HFTs in order to court their
order flow.” “It was the first credible evidence of Big Foot,”
said Matt. He dug around on his own and saw that the glitches
at BATS and Nasdaq that queered the market for the benefit
of HFT weren’t flukes but symptoms of a systemic problem,
and that “many other little market quirks were there that were
potentially being exploited.”
He was then in an awkward position: that of a public spokes-
man for the new American-style stock market who doubted the
integrity of that market. “I’m at the point where I no longer feel
I can authentically defend high-frequency trading,” he said. “I
look at us exporting our business model to all these different
countries and I think. It’s like exporting a disease .” He was thirty-
four years old, and married, with a one-year-old child. Chi-X
was paying him more than $400,000 a year. And yet, with no
idea what he was going to do to earn a living, he up and quit.
“I don’t want to say I’m an idealist,” he said. “But you have a
limited amount of time on this planet. I don’t want to be twenty
years from now and thinking I hadn’t lived my life in a way I
could be proud of.” He kicked around for the better part of a
year before he thought to call Ronan, whom he’d met when
Ronan came through to run cables for HFT inside his Canadian
exchange. In October 2012 they met for coffee at the McDon-
ald’s near Liberty Plaza, and Ronan explained he’d just left RBC
to open a new stock exchange. “My first reaction was, I feel so
bad for the guy,” said Matt. “He’s just destroyed his future. They’re just
doomed. Then, afterwards, I asked myself, ‘What causes a bunch
of people making a million a year to quit?’ ” He came back in
November and asked Ronan some more questions about this
new exchange. In December, Brad hired him.
Standing in front of the whiteboard, Brad now reviewed the
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problem at hand: It was unusual for an investor to direct his bro-
ker to send his order to one exchange, but that is what investors
were preparing to do with IEX. But these investors had no way of
determining if the Wall Street brokers followed their instructions
and actually sent the orders to IEX. The report investors typi-
cally received from their brokers — the Transaction Cost Analy-
sis, or TCA — was useless, so sloppily and inconsistently compiled
as to be beyond analysis. Some of it came time-stamped to the
second; some, time-stamped in tenths of microseconds. None of
it told you which exchange you traded on. As a result, there was
no way to determine the context of any transaction, the event
immediately before it and the one immediately after. If you didn’t
even know the order of the trades in the stock market, you could
hardly determine if you had traded at a fair price. “It’s a Pandora’s
box of ridiculousness,” said Brad. “Just getting an answer to the
question: ‘Where did I trade?’ It isn’t really possible.”
“What if they [investors] send us their trade orders and we
check them to see if they ever got here?” asked Rob Park sensibly.
“We can’t,” said Don. “It violates our confidentiality agree-
ment with brokers.”
True. An investor might hand Bank of America an order and
ask the Bank of America broker to route it to IEX. The inves-
tor might also ask that IEX be permitted to inform him of the
outcome. And yet Bank ol America might refuse, on principle,
to allow IEX to inform the investor that they had followed his
instructions — on the grounds that doing so would reveal Bank
of America’s secrets!
“Why can’t we just publish what happened?” asked Ronan.
“It’s the banks’ information,” said Don.
“We can't publish what happened to an investor’s trade because
what happened to the investor is Goldman Sachs’s information?”
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187
Ronan was incredulous — but then he knew less about this than
the others.
“Correct.”
“What can they do to us if we do it — shut us down?”
“Probably just a slap on the wrist the first time,” said Don.
Brad wondered aloud if it was possible to create a mechanism
through which investors might be informed, in real time, where
their brokers sent their stock market orders. “Like a security
camera,” he said. “You don’t care if it’s even turned on. Just the
fact that it’s there might alter behavior.”
“It’s a finger in the eye of the brokerage community,” said
Don. He wore a t-shirt that said I Love Aquatic Life, and tossed
a rugby ball to himself, but he didn’t feel as comfortable as he
wished to appear. All these other guys had worked at big Wall
Street banks; none of them had ever had to deal with those
banks as a customer. They didn’t know their market power. As
Don later put it, “The brokers, if they all decide to hate us, we’re
fucked. End of story.” He didn’t put it so bluntly to the others,
maybe because he sensed that they all knew it.
“It's like saying, ‘I think people are stealing in this office,’”
said Brad, with growing enthusiasm. “I can run in and run out
and run in and run out and keep checking and try to catch
someone. Or I can install a camera. It may be plugged in — or
not. But there’s still this camera. And whoever is fucking steal-
ing my coffee pots won’t know if it’s on.”
“We don’t really give a fuck if the investors use it,” added
Ronan. “We just want the brokers scared they’ll check.”
Somewhere in the big room a phone rang, and the sound was
as jolting as a car honking in a small town in the middle of the
night. The room was an open pit, with no barriers between
the people in it, but the young men inside it behaved as if they
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worked with walls around them. They were, all but one, young
men. The exception, Tara McKee, had been a research associate
at RBC until Brad found her, in 2009, and asked her to be his
personal assistant. (“The first time I met him, I said, ‘I don’t care
what I do — I just want to work for him.’ ”) She’d followed him
out when he left the bank, even after he tried to talk her out
of it, as he couldn’t pay her properly and didn’t think she could
tolerate the risk. The cast of technologists Brad had assembled at
this new place Tara found even more peculiar than the one he’d
put together at RBC. “For geniuses, they are really dumb,” she
said. “Some of them are really pampered: They can’t even put
together a cardboard box. They don’t think you do something.
They think you call somebody.”
They were also amazingly self-contained. This meeting con-
cerned them all— compelling the big Wall Street banks’ coopera-
tion might mean the difference between success and failure — but
they all at least feigned indifference. The etiquette here was a kind
of willed incuriosity — even about each other. “Communication
with a lot of the guys is not that great,” said Brad. “It’s something
we need to work on.” It was funny. To a man, they were puzzle
solvers, and yet, to each other, they remained unsolved puzzles.
Schwab looked over the desks and shouted, “Whose phone is
that?”
“Sorry,” someone said, and the ringing stopped.
“It’s a nanny,” said Don, of Brad’s security camera idea. “It’s
demeaning. It could be a strain on the relationship.”
“When you get patted down in the airport, do you hate the
people who pat you down?” asked Brad.
“I fuckin’ hate them,” said Don.
“I say, ‘I’m glad you’re checking my bags, because that means
you’re checking other people’s,’ ” said Brad.
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189
“The problem is that everyone is carrying marijuana through
the checkpoint,” said Schwab.
“If anyone gets fucking angry it’s because they’re guilty,” said
Brad hotly.
“I’m sorry,” said Don. “I’m fat and white and I’m not gonna
bomb this airplane. I shouldn’t get extra swabbing.” He’d stopped
tossing the rugby ball.
“Is there some use for this other than policing brokers?” asked
Schwab. He was asking, “Can we police them without their
realizing it?” The person among them most adept at uncovering
the secrets of others believed it was possible for IEX to keep its
own affairs secret.
“No,” said Brad.
“So it’s a nanny,” said Schwab with a sigh.
“Broker Nanny,’ 1 said Don. “It’s a great name. Shame we can’t
patent it.”
The meeting went quiet. This was just one of a thousand
arguments they’d had in designing the exchange. The group was
roughly split — between people (Ronan and, to a lesser extent,
Brad) who wanted to pick a fight with the biggest Wall Street
banks, and people who thought it was insane to pick that fight
(Don and, to a lesser extent, Schwab). Rob and Matt hadn’t yet
come clean, but for different reasons. After his initial suggestion
had been swatted away, Rob had gone silent. “Rob is farthest
from the chaos,” said Brad. “He doesn’t meet with brokers. The
solutions to the problems they [the Wall Street brokers] create
are illogical because they solve a problem that is illogical.”
Matt Trudeau, also quiet, often tended to step back and
observe. “I’ve always felt a little outside the groups of people
I hung around with,” he said. He was a natural conciliator as
web. He may have quit his job on principle, but he didn’t enjoy
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conflict, even the internal kind. “I might not be jaded enough,”
Matt now said carefully. “But let’s say we launch and we’re
wildly successful and we never have to roll this out.”
That thought was dead on arrival: No one believed they
would be wildly successful the moment they launched— least
of all Matt. He knew firsthand what happened when a new
exchange opened: nothing. Chi-X Canada was now a huge
success — 20 percent of the Canadian market — but in its first
month it had traded 700 shares total. Entire days passed with-
out a single trade on that exchange; and the next few months
weren’t much better. And that was what success looked like.
IEX didn’t have the luxury of going months without activity.
Their new stock exchange didn’t need to be an instant sensa-
tion, but it had to host enough trading to illustrate the positive
effects of honesty. They needed to be able to prove to inves-
tors that an explicitly fair exchange yielded better outcomes for
investors than all the other exchanges. To prove the case, they
needed data; to generate that data, they needed trades. If the
big Wall Street banks colluded to keep trades off IEX, the new
exchange would be stillborn. And they all knew it.
“They’re gonna be pissed,” said Schwab finally.
“We’re in a fight,” said Brad. “If every client felt like their
instructions were being followed, we wouldn’t be having this
discussion. It’s not about IEX wanting to go punch some bro-
ker in the face for no reason. It’s not about saying, Who is our
enemy?’ It’s about saying who we are aligned with. We’re aligned
with the investor.”
“They’re still gonna be pissed,” said Schwab.
“Are we really in the police business?” asked Don.
“Maybe we don’t have to have it at all,” added Schwab.
“Maybe we just have to create the illusion we have it. We talk to
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191
the buy side about having it, and they whisper to their brokers —
that might be enough.”
“But they’ll all know,” said Don. “They know we have to
keep the brokers’ junk private. And the broker has to keep the
clients’ junk private. And the client can’t opt out.”
Brad offered one last idea: a chat room in which investors
could converse with their brokers as the trade was happening.
“Or they can always get their broker on the phone and say, ‘Tell
me what the fuck is going on,’ ” he said. “It’s always been a
solution.”
“They’ve never done it,” said Ronan.
“They’ve never been motivated to do it,” said Matt. True:
Investors had never been given a compelling reason to favor one
stock exchange over another.
“You get Danny Moses in a chat room with Goldman,” said
Brad, referring to the head trader at Seawolf. “He’ll ask them.”
“But Danny’s a bit argy-bargy,” said Ronan.
“ Argy-bargy , I like that,” said Don.
Ronan had been teaching Don Irish epithets, one at a time.
“You got wanker. Tosser. Now you got argy-bargy,” said Ronan.
“You do nothing, and everyone does what they want,” said
Brad. “You do something and you can influence behavior. But,
by creating the tool, do we incentivize behavior we want to
eliminate? By shining the light, do we create a gray zone, just
outside the light? Is it like Reg NMS, where you create the very
thing you’re trying to get rid of?”
“Shining a light creates shadows,” said Don. “If you try to
create this bright line, you are going to create gray zones on
either side.”
“If we sincerely believe it creates too many blind spots, we
might not want to do it,” said Brad.
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“If we bill it as a nanny and she’s drunk on the couch, are we
gonna look like assholes?” added Don. “Better not to have a
nanny at all. Just leave the kids home alone.”
“If you can think of any other possible use for this fucker,
that would help,” said Schwall, who clung to his hope that they
might disguise their actions. That they might be secret cops.
“I’m less bullish on this than I was before,” said Brad. “I’ll
be honest. Because a drunk nanny might not be better than no
nanny at all.”
“How drunk can a nanny get?” asked Ronan idly.
Brad tossed the marker back into the whiteboard bin. “You
can see why the client has been left in the dust,” he said. “The
system is designed to leave the client in the dust.” Then he
turned to Don. “At Nasdaq did they talk about this?”
“No,” said Don, leaning back against the window.
For a moment, Brad looked at Don, and at the view that he
only partly concealed. In that moment, he might as well have
been, not on the inside of his new exchange looking out, but
on the outside looking in. How did they seem to others? To the
people out there ? Out there, where the twin symbols of American
capitalism once loomed, reduced in a few hours to a blizzard of
office memos and a ruin. Out there, where idealism was either
a ruse or a species of stupidity, and where the people who badly
needed them to succeed hadn’t the faintest idea of their exis-
tence. But out there a lot of things happened. People built new
towers to replace the old ones. People found strength they didn’t
know they had. And people were already coming to their aid,
and bracing for the war. Out there, anything was possible.
CHAPTER SEVEN
AN ARMY OF ONE
O n the morning of September 11, 2001, Zoran Perkov
took the subway from his home in Queens to Wall Street,
as he did every day. As usual, he wore headphones and
listened to music, and pretended that the other people on the
train didn’t exist. The difference between that morning and all
the others was that he was running late, and the people on the
train were harder than usual to ignore. They were talking to each
other. “Nobody talks to each other,” said Zoran. “It was a weird
feeling, when you feel something is off.” He was twenty-six
years old, tall and broad, with hooded eyes that saw everything
in one shade of gray or another. Born in Croatia, into long lines
of fishermen and stonemasons, he’d moved with his parents to
the United States when he was a small child. He’d grown up
in Queens, and he worked on a tech help desk for the crypti-
cally named Wall Street Systems, at 30 Broad Street, immedi-
ately next door to the New York Stock Exchange. His job bored
him. What precisely he did on Wall Street Systems’ tech help
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desk didn’t matter. He wouldn’t be doing it much longer. In
the next few hours, he’d discover a reason for doing something
else. This discovery — and the clear sense of purpose that came
with it would put him on a course to be of serious use to Brad
Katsuyama.
The subway car was a silent movie. Zoran watched the people
in it talking to each other all the way to Wall Street. Ascending
from the hole in the ground in front of Trinity Church and into
the morning light, he noticed the necks tilted back and the eyes
gazing upward. He, too, looked up, just as the second plane hit
the South Tower. “You couldn’t see the plane,” he said. “You
just saw this explosion.”
He took off his headphones and heard the sounds. “All around
people crying, people screaming, people puking.” He saw peo-
ple running up Broadway. He crossed the street and went to
work. Work isn t work for me,” he said. “I got friends there. I
went to find out what is going on.” Outside the front door, he
spotted the same pretty woman with a cigarette he always saw
on his way in. (“You know, the one hot chick in the building.”)
She was smoking but also crying. He went upstairs, checked
in with his friends, and called some guys he’d grown up with
who worked on or around Wall Street. One of them worked in
the Twin Towers — which tower Zoran couldn’t recall. A couple
more worked in the buildings around the towers. He reached
them and they agreed to use his office as their meeting point.
When his friend from the Twin Tower arrived, he said that on
his way out he’d heard the bodies hitting the ground.
The small group of five friends set out to escape. They dis-
cussed strategy. Zoran argued for walking out, up Broadway;
the others voted to leave on the subway. “Democracy won,” said
Zoran, and back down into the Wall Street station they went. It
AN ARMY OF ONE
195
turned out that this was not an original idea. The crowds forced
them apart; three of them squeezed into one car, while Zoran
and another pushed into the next car. “It was such a mixed
crowd,” said Zoran, “not your usual subway crowd.” There
were all these Wall Street people; guys from the stock exchange
in their colored jackets; people you just never saw there. The car
lurched out of the station and into the dark tunnel, then stopped.
“That’s when my ears popped,” said Zoran. “Like when you go
swimming under water.”
The tunnel tilled with smoke. Zoran had no idea what had
happened — why his ears had popped, why the tunnel was full
of smoke — but he noticed a guy trying to open a window, and
he hollered at him to stop. Who gave you the authority? the guy
screamed back at Zoran. “It’s smoke'' Zoran shouted. “Breathe
it. Die. It’s that fucking simple.” The window stayed shut, but
the car remained fractious and unsettled. The car holding his
other friends was tranquil. People bent over, praying.
The conductor came on and announced that the train needed
to return to the Wall Street station. To general concern, the guy
who drove the tram walked from the front car to the back car,
did whatever needed to be done to allow the train to go the
wrong way inside a tunnel, and jolted it back Irom whence it
had come. But not completely: Only the front two cars gained
access to the platform. The people in what was now the rear of
the train needed to file out through the cars to reach the exit.
That’s when Zoran noticed the old man — his neighbor, in a
crowd trying to form a line to exit the train. “He’s got a cane,”
said Zoran. “He’s in an old suit — he’s gotten thinner and smaller,
so it doesn’t fit him very well. I remember thinking: I should
probably make sure this guy doesn’t get crushed. So I just kind of kept
him in front of me. I felt responsible for him.” Half-guiding the
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old man, he nudged his way back up the steps of the subway sta-
tion and onto Wall Street. Then everything went totally black.
“We get to street level, and I had to realize it was street level,”
said Zoran. And I lost the old guy. From that moment I was just
paying attention to everything around me.”
He now couldn’t see, but he could hear people shouting.
“Over here! Over here!” he heard someone scream. He and
the friend who’d been in the subway car with him followed
the sound of the voices, walking into what turned out to be
the American Express building — though Zoran didn’t realize it
until they’d been inside for a minute. What he noticed was the
pregnant woman, sitting on the floor with her back against a
wall. He went to her, made sure she wasn’t about to give birth,
then gave her his phone, which still worked. The black air out-
side began to acquire a color. “For some reason everything had
this beige-like tone, ’ he recalled. He could now see more or less
where they were, and which direction was which. A cop inside
the building said, You need to stay in here.” Zoran grabbed his
triend and left. They walked east and north until they arrived at
some faceless apartment buildings on the Lower East Side. “It’s
the projects, said Zoran, “and people are coming out with cups
of water and all of their cordless phones. To help. That’s when I
started to cry.”
Eventually they reached the FDR Drive and continued due
north. That might have been the oddest feeling of the entire
morning, that walk along a stretch of the FDR. They were
alone. It was quiet. For an amazingly long time, the only human
being they encountered was a half-dressed cop who roared past
them on a motorbike toward the catastrophe. Then the papers
began to flutter down from above. On them Zoran could read
the address of the World Trade Center.
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197
To say that Zoran found the whole experience exhilarating —
well, that wouldn’t be quite right, though, as he told his story,
he said that “somehow I feel guilty about telling it.” It was more
that there hadn’t been even a moment when he had felt he didn’t
know what he should do next. He’d been jarred into a new kind
of awareness, and interest in the people around him, and he liked
the feeling. His reactions had surprised him into an observation
about himself. “I was impressed that I did not fall apart,” he said.
“I didn’t use it as an excuse for anything. What it tells me is that
I wasn’t afraid of those situations. I like being front and center. I
like being in a drama.” He could even pinpoint the moment he
realized he was better suited to a crisis than he expected himself
to be. “It was when I realized I’ve started to give a shit about
other people,” he said.
Two days later he returned to work, but he’d been biffed from
an ill-defined career path onto another, clearer one. He wanted
to be in a job that required him to perform in a crisis. If you
worked on the technology end of Wall Street and were looking
for pressure, you ran an electronic stock market. By early 2006,
that’s what Zoran was doing — at Nasdaq. “They just sat me in
front of four machines with buttons that could, like, destroy
everything,” he said. “It was the best thing in the world. Every
day was the Super Bowl. The value of what you were doing felt
so high.” The feeling of the job was hard to get across to anyone
who wasn’t a technologist, but there was definitely a feeling to
it. “Put it this way,” said Zoran. “If I fuck up, I’m going to be in
the news. I’m the only one who can break it, and if it breaks I’m
the only one who can fix it.”
He’d learned this the hard way, of course. Not long after he
started at Nasdaq, he’d broken one of the markets. (Nasdaq has
owned several markets — Nasdaq OMX, Nasdaq BX, INET,
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PSX.) It happened when he was making changes to the system
during trading hours. He entered a command, then heard the
people around him panicking; but he failed to immediately con-
nect one event to the other. A former Nasdaq colleague recalled
the ensuing bedlam. I remember seeing people running around
and screaming while it was happening,” he said. Zoran looked up
at the stock market on his computer screen: It was frozen. It took
him a few seconds to realize that, even though the thing he’d
been working on should have had no connection to the market
in real time, he had somehow shut his entire market down. It
took him another few seconds to see exactly how he had done
it. Then he fixed it, and the market resumed trading. From start
to finish the crisis had lasted twenty-two seconds. Twenty-two
seconds, during which all trading had simply ceased. “I remem-
ber sitting there and thinking: I’m done,” said Zoran. “The CTO
[chief technology officer] saved me. He said, ‘How can you get
rid of a guy who makes a mistake, stops it, and fixes it?’ ”
Still, the event shaped him. “I said, ‘How do I never do that
again? said Zoran. “I started really jumping into how to control
large-scale complex systems. I became a student of complexity —
defined as something you cannot predict. How do you have
stability in a system that is by its nature unpredictable?” He read
everything he could find on the subject. One of his favorite
books was actually called Complexity, by M. Mitchell Waldrop.
His favorite paper to pass out was “How Complex Systems Fail,”
an eighteen-bullet-point summary by Richard I. Cook, now a
professor of health care systems safety in Sweden. (Bullet Point
#6: Catastrophe is always just around the corner.) “People think that
complex is an advanced state of complicated,” said Zoran. “It’s
not. A car key is simple. A car is complicated. A car in traffic is
complex.”
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199
A stock market was a complex system. One definition of a
complex system was a place where, as Zoran put it, “Shit will
break and there is nothing you can do about it.” The person
whose job it was to make sure shit didn’t break ran two kinds
of career risks: the risk of shit breaking that was within his con-
trol, and the risk of shit breaking over which he had no control.
Zoran continued to run one of the Nasdaq markets. Eventually,
the company handed him bigger markets to run; and the risk
of running them grew. By the end of 2011, he was overseeing
all of Nasdaq’s market running. (Head of Global Operations,
he was called.) He had spent the better part of six years add-
ing complexity to those markets, for reasons he did not always
understand. The business people would just decide to make
some change, which it was his job to implement. “The Post-
Only order type was the first thing that got me,” said Zoran,
of the order designed to be executed only if the trader received
a kickback from the exchange. “What the fuck is the point of
a Post-Only order?” He was somehow expected to cope with
the demands made on Nasdaq’s markets by Nasdaq’s biggest
customers (high-frequency traders) and, at the same time, keep
those markets safe and stable. It was as if a pit crew had been
asked to strip down the race car, rip out the seat harnesses, and
do whatever else they might to make the car go faster than it
ever had before — and at the same time reduce the likelihood
that the driver would die. Only in this case, if the driver was
killed, blame for his death would be assigned, arbitrarily, to one
member of the pit crew. Him.
This state of affairs led to a certain skittishness in the pit crew.
It wasn’t just that the high-frequency traders were demanding
changes to the market that would benefit only them: The mere
act of changing the system increased the risks to everyone who
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depended on it. Adding code and features to a trading system
was like adding traffic to a highway: You couldn’t predict the
consequences of what you had done; all you knew was that you
had made the situation more difficult to understand. “No one is
trying to control what they don’t know,” said Zoran. “And what
they don’t know is growing.” He thought of himself as good in
a crisis, but he didn’t see the point of manufacturing crises so
that he might demonstrate his virtuosity. He was also far less
suited to managing a bunch of market runners than he was to
running a market himself. He had no gift for corporate politics.
Every day, he liked his job less and less — until, in March 2012, he
was fired, whereupon he got a phone call from Don Bohemian.
Don wanted Zoran to run the market for IEX. “I’m not going
to pitch you just now, mainly because we have no money and we
don’t even know what we’re going to do,” said Don. “But I may
pitch you later. ’ Don knew that Zoran had been a casualty of an
office political battle, and, more to the point, that he was maybe
the best exchange runner he’d ever seen. “He has all the quali-
ties,” said Don. “Poise under pressure. The ability to understand
a complex and vast system. And be able to think into it — imagine
into it — accurately. To diagnose and foresee problems.”
It was a little unsettling that the geeks who now ran the
financial markets were also expected to have the nerves of a test
pilot. But by the time Don approached Zoran, it had grown
clear that the investing public had lost faith in the U.S. stock
market. Since the flash crash back in May 2010, the S&P index
had risen by 65 percent, and yet trading volume was down 50
percent: For the first time in history, investors’ desire to trade
had not risen with market prices. Before the flash crash, 67
percent of U.S. households owned stocks; by the end of 2013,
only 52 percent did: The fantastic post-crisis bull market was
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noteworthy for how many Americans elected not to participate
in it. It wasn’t hard to see why their confidence in financial
markets had collapsed. As the U.S. stock market had grown less
comprehensible, it had also become more sensationally erratic.
It wasn’t just market prices that were unpredictable but the mar-
ket itself — and the uncertainty it created was bound to extend,
sooner or later, to the many foreign stock markets, bond mar-
kets, options markets, and currency markets that had aped the
U.S stock market’s structure.
In March 2012 the BATS exchange had to pull its own initial
public offering because of “technical errors.” The next month,
the New York Stock Exchange canceled a bunch of trades by
mistake because of a “technical glitch.” In May, Nasdaq bungled
the initial public offering of shares in Facebook Inc. because, in
essence, some investors who submitted orders to buy those shares
changed their minds before the price was agreed upon — and
certain Nasdaq computers couldn’t deal with the faster speeds at
which other Nasdaq computers allowed the investors to change
their minds. In August 2012, the computers of the big HFT firm
Knight Capital went berserk and made stock market trades that
cost Knight $440 million and triggered the company’s fire sale.
In November, the NYSE suffered what was termed a “match-
ing engine outage” and was forced to halt trading in 216 stocks.
Three weeks later, a Nasdaq employee clicked the wrong icon
on his computer screen and stopped the public offering of shares
in a company called WhiteFlorse Finance. In early January 2013,
BATS announced that, because of some unspecified computer
error, it had, since 2008, inadvertently allowed trades to occur,
illegally, at prices worse (for the investor) than the National Best
Bid and Offer.
That was just a sampling from a single year of what were usu-
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ally described as “technical glitches” in the new, automated U.S.
stock markets: Collectively, they had experienced twice as many
outages in the two years after the flash crash as in the previous
ten. The technical glitches were accompanied by equally bewil-
dering irregularities in stock prices. In April 2013, the price of
Google’s shares fell from $796 to $775 in three-quarters of a
second, for instance, and then rebounded to $793 in the next
second. In May the U.S. utilities sector experienced a mini-flash
crash, with stocks falling by 50 percent or more for a few seconds
before bouncing back to their previous prices. These mini-flash
crashes in individual stocks that now occurred routinely went
largely unnoticed and unremarked upon.*
Zoran liked to argue that there were actually fewer, not more,
“technical glitches” in 2012 than there had been in 2006 — it
was only the financial consequences of system breakdowns that
had grown. He also took issue with the word “glitch.” (“It’s the
worst word in the world.”) When some machine malfunctioned
and a stock market came under scrutiny, the head of that mar-
ket usually had no clue either what had happened or how to
fix it: He was at the mercy of his technologists. But he had to
say something, and so he said that there had been a “technical
glitch.” It was as if there was no way to explain how the financial
market actually worked — or didn’t — without resorting to fuzzy
* Eric Hunsader, the founder of Nanex, a stock market data company, is a fantastic
exception to the general silence on this subject. After the flash crash, it occurred to
him to use his data to investigate what had gone wrong, and the search never really
ended. “Almost every rock t overturn, something nefarious crawls out from under it,”
he said. Hunsader has brilliantly and relentlessly described market dysfunction and
pointed out many strange micro-movements in stock prices. When the last history of
high-frequency trading is written, Hunsader, like Joe Saluzzi and Sal Arnuk of The-
mis Trading, deserves a prominent place in it.
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metaphors and meaningless words * If stock market computer-
related problems were to be reduced to a single phrase, Zoran
preferred it to be “normal accidents.”' 1 "
When Bollerman called him again, late in the summer of
2012, IEX had an idea, and the first glimmer of hope that they
would find money. That the idea was also idealistic made Zoran
skeptical; he wasn’t sure it was possible ever to make a financial
market fair. But he absolutely loved the idea of running a mar-
ket he helped to design — to limit the number of things in it he
could not control. He came in to IEX to meet Brad and Rob
and John Schwall and Ronan. Brad and Schwab and Rob liked
him, Ronan not so much. “What put me off is that he wouldn’t
shut the fuck up,” said Ronan.
His first few months on the job, Zoran drove everyone nuts.
Lacking a market crisis, he proceeded to create a social one.
They’d tell him about some new feature they had thought to
introduce into the system and ask, “Will this make the system
harder to manage?” To which Zoran would reply, “It depends
on your definition of ‘harder.’ ” Or they would ask him if some
small change in the system would cause the system to become
less stable — to which Zoran would reply, “It depends on your
definition of ‘stable.’ ” Every question he answered with an
uneasy chuckle, followed by some other question. A rare excep-
tion came when he was asked, “Why do you always answer a
question with another question?” “Clarity,” he said.
Zoran also seemed to assume that his new colleagues would
* “Glitch” belongs in the same category as “liquidity” or, for that matter, “high-
frequency trading.” All terms used to obscure rather than to clarify, and to put minds
to early rest.
f From a book of that name by Charles Perrow.
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fail to understand the difference between what he could control
and what he couldn’t. In one thirty-day span after he joined IEX,
he shot out fifteen emails on this one subject — to hammer home
the mystery inherent in any stock market technological failure.
He even invited a speaker to come in to reinforce the point.
“It was one the few times that the people in the room wound
up at each other’s throats,” said Brad. “The tech people were
all agreeing with him, and the business people were saying, ‘If
something melts down, how could it not be someone’s fault?’ ”
Brad’s breaking point came after the guest speaker had left and
Zoran circulated a blog post called “A Short Story on Human
Error.” The gist of it was that when complex systems broke, it
was never the fault of any one person. The post described some
computer catastrophe and then concluded, . . you’ll notice
that it wasn’t just one little thing that caused it. It wasn’t the
developer who just so happened to delete the wrong table. It was
a number of causes that came together to strike hard, all of them
very likely to be bigger issues inside the organization rather than
a problem with the individual.” At which point Brad finally
walked the ten yards from his desk to Zoran’s desk and shouted,
“Stop sending these fucking emails!”
And he did, finally. “I know what to do when things are
exploding around me,” he later said. “But when nothing is
exploding, the overthinking comes into play.”
Initially Brad was mystified: How could a guy who thrived
under pressure also have such a fear of being blamed if things
went wrong? “He’s so good in a crisis,” said Brad later. “In
game-time situations. Under pressure. I’ve seen it. But it’s like
a quarterback who is great in the game, then spends the other
six days explaining how it isn’t his fault if he throws an inter-
ception. ‘Dude, your passer rating is 110. Stop it .” ’ Brad realized
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something: “It comes from a sense of insecurity that comes from
the fact that he will be more recognized when things go wrong
than when things go right.” Brad further realized that the prob-
lem was not peculiar to Zoran but general to Wall Street tech-
nologists. The markets were now run by technology, but the
technologists were still treated like tools. Nobody bothered to
explain the business to them, but they were forced to adapt to its
demands and exposed to its failures — which was, perhaps, why
there had been so many more conspicuous failures. (The excep-
tion was the high-frequency trading firms, where the technolo-
gists were kings. But then, the HFT firms didn’t have clients.)
Nasdaq’s famously talented engineers were an extreme Wall
Street case. The constant pressure on Nasdaq’s tech guys to adapt
the stock markets’ code to the needs of high-frequency trad-
ers had created a miserable, politicized workplace. The Nasdaq
business guys foisted all these unreasonable demands on the tech
guys and then, when the demands busted the system, blamed
the tech guys for the failure. The tech guys all wound up with
this abused animal quality to them. “You just have to unabuse
them,” Brad explained, “and let them know they aren’t going to
be blamed just because something goes wrong.” We all know that
things will go wrong and it isn’t necessarily anyone’s fault.
Rob and John Schwab seemed to agree that this was the
correct approach to take with the people they hired from Nas-
daq: to tell them over and over that they weren’t to blame for
whatever had just happened, to include them in every business
discussion so that they could see why they could be a part of
it, and so on. Ronan had no patience for any of it. “C’mon,
they came from a corporate American job,” he said. “They
didn’t come from Auschwitz.” On the other hand, in time,
even Ronan saw that Zoran possessed useful qualities he hadn’t
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at first perceived. “Someone who will be good at running the
market — you need to be the most paranoid fuck in the world,”
said Ronan. “And he’s the most paranoid fuck in the world.
He thinks ten steps down the road of what could go wrong —
because he’s thinking of what could happen to him if it goes
wrong. He’s really good at it.”
On the morning of October 25, 2013, Zoran Perkov took the
subway from his home to Wall Street, as he always did. As usual,
he read some book or white paper, and tried to pretend that the
people around him didn’t exist. The difference between that
morning and the others was that he was running early and had
a stock market to open — and it was unlike any market he’d ever
run. Spare, clean, single-minded, and built from the ground up
by people he not only admired but now trusted. “Every single
morning, the system is stateless,” he said, of exchange matching
engines generally. “It doesn’t know what it’s supposed to do.
Ninety-nine percent of the time, it’s the same thing it did the
day before.” On this day, that could not possibly have been true,
as the IEX matching engine had never actually done anything.
Zoran sat down at his desk in IEX’s office and punched a few
buttons and watched code scroll down his screen. He pulled out
an old, battered computer mouse — then noticed it was dead. He
frowned. “It’s my war mouse,” he said. “Every single market I
have opened in the past ten years has been with this mouse.” He
knocked it against the desk, realized that its battery had probably
died, and wondered, briefly, how to replace it. “My wife mocks
me because I can’t work the microwave oven but I can run a
market,” he said. He switched out his war mouse for another,
and checked his computer screens. The seconds ticked down;
it was approaching nine thirty in the morning, when the U.S.
stock market would open and, with it, this new market inside of
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it that aimed to transform it. He waited and watched for some-
thing to go wrong. It didn’t.
A minute before nine thirty, Brad walked over to Zoran’s
desk: By popular agreement, Brad was to open the market that
first day. He looked down at the keyboard, perplexed.
“What do I do?” he asked.
“Just hit Enter,” said Zoran.
The entire room counted down the final seconds before the
opening.
“Five . . . four . . . three . . . two . . . one.”
Six and a half hours later, the market closed. Zoran had no
idea whether the market as a whole had finished up or down for
the day. Ten minutes after that he could be found, alone, pacing
outside the 9/11 memorial, smoking a cigarette. “This is like the
first day of the battle against complacency,” he said.
TWO AND A half months later, sixteen people — the chief execu-
tives or the head traders of some of the world’s biggest stock
market money managers— gathered in a conference room on
top of a Manhattan skyscraper. They’d flown in from around the
country to hear Brad describe what he’d learned about the U.S.
stock market since IEX had opened for trading. From that trad-
ing, he’d gotten new information. To afford people interested in
the truth even a glimpse of it was now considered faintly sedi-
tious.* “This is the perfect seat to figure all this out,” said Brad.
* In March 2013, the Commodity Futures Trading Commission, a derivatives regulator,
ended its nascent program to give outside researchers access to market data after one of
those researchers, Adam Clark-Joseph, of Harvard University, used the data to study the
tactics of high-frequency traders. The commission shut down the research after lawyers
for the Chicago Mercantile Exchange wrote the regulators a letter arguing that the data
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“It’s not like you can stand outside and watch. We had to be in
the game to see it.”
The sixteen investors controlled roughly $2.6 trillion in stock
market investments among them, or roughly 20 percent of the
entire U.S. market. Collectively, they paid to the big Wall Street
banks roughly $2.2 billion of the $11 billion a year the Street
earned from stock market commissions.* They weren’t exactly
of one mind or spirit. A few of them were also investors in
IEX, but most were not. A couple held the knowing, seemingly
grown-up view that it was naive to think that idealism could
have any effect on Wall Street. A few thought it was important
to remember that technology had lowered their trading costs
from what they had been decades earlier — and half-turned a
half-blind eye to the stunts Wall Street intermediaries had pulled
to prevent technology from lowering those costs even further.
But whatever their predispositions, they were all at least a little
bit angry, because they all had spent the past few years listening
to Brad’s descriptions of the inner workings of the U.S. stock
market. They now thought of him less as a guy trying to sell
them something than as a partner, in a possibly quixotic attempt
to fix a financial system that had become deeply screwed up.
“You kind of know what’s going on, but you don’t have a good
explanation for it,” said one. “He gave us the explanation.” A
second said, “This isn’t about execution. It’s about a movement.
Clark-Joseph had collected belonged to the high-frequency traders, and that sharing it
was illegal. Before he was booted out of the place, Clark-Joseph showed how HFT firms
were able to predict price moves by using small loss-making stock market orders to glean
information from other investors. They then used that information to place much bigger
orders, the gains from which more than compensated for the losses.
* Estimates of commission paid to Wall Street banks for stock market trades in 2013
range from $9.3 billion (Greenwich Associates) to $13 billion (the Tabb Group).
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I’m sick and tired of getting fucked. When I go into the market
I want to know it’s clean.” A third added, “All of a sudden the
market is all about algos and routers. It’s hard to figure this stuff
out. There’s no book you can read. It’s just calling up people and
talking to them. From the people at the banks you can’t get a
straight answer to any question. You say, ‘The sky is blue.’ They
say, ‘The sky is green.’ And you’re like, ‘What are you talk-
ing about?’ And after half an hour it comes out that they have
changed the definition of ‘sky.’ You know what you’re asking.
They know what you’re asking. But they don’t want to answer
it. The first time I talked to Brad and he was telling me how it
all actually worked, my jaw must have hit the floor.”
Another investor had a question about Brad. “Why does a
person take the harder path? It’s a different situation from what
you typically see. If it works, he will make money. But he’ll
make less” than if he had stayed at RBC.
The sixteen were all men. Most wore suits, with deep creases
on the backs of their jackets that looked as if they’d been made
with a bullwhip. They were different from the people who
worked at the big Wall Street banks, and from the HFT guys.
They were a lot less likely to bounce from firm to firm — a lot
more likely to have a career in one place. They were more iso-
lated, too: They didn’t know each other well and didn’t, until
Brad suggested it, have any reason to organize themselves into
any kind of fighting force. Many had just landed in New York
City, and a few of them were obviously weary. Their tone was
informal and familiar, with none of the usual jockeying for sta-
tus. They might not all have been capable of outrage, but they
were all still capable of curiosity.
At some level, they all now realized that this thirty-five -year-
old Canadian guy somehow had put himself in a position to
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understand the United States stock market in a way that the
system, possibly, had never been understood. “The game is
now clear to me,” Brad said. “There’s not a press release I don’t
understand.” On August 22, Nasdaq had experienced a two-
hour outage caused by what they said was a technical glitch
in the SIP. Brad thought he understood why it had happened:
Nasdaq threw vast resources into the cool new technology used
by HFT to speed up its trading and little into the basic plumbing
of the market used by the ordinary investor. “Nasdaq’s got this
state-of-the-art facility for HFT,” he said. “Seventeen-kilowatt
liquid-cooled cabinets and cross-connects everywhere and all
this shit, and then they have this single choke point in the entire
market — the SIP — and they don’t care about it. The B team is
servicing it.” Four days later, two of the public exchanges, BATS
and Direct Edge, revealed their intention to merge. In a normal
industry, the point of a merger of two companies that performed
identical functions would be to consolidate — to reduce costs.
But, as a subsequent press release explained, both exchanges
intended to remain open after the merger. To Brad the reason
was obvious: The exchanges were both at least partially owned
by high-frequency trading firms, and, from the HFT point of
view, the more exchanges the better.
A few weeks later, both Nasdaq and the New York Stock
Exchange announced that they had widened the pipe that carried
information between the HFT computers and each exchange’s
matching engine. The price for the new pipe was $40,000 a
month, up from the $25,000 a month the HFT firms had been
paying for the old, smaller pipe. The increase in speed was two
microseconds. Brad understood that the reason for this was not that
the market was better off if HFT had information two microsec-
onds faster than before, but that the high-frequency traders were
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all terrified of being slower than their peers, and the exchanges
had figured out how to milk this anxiety. In a stock market now
defined by its technology accidents, nothing actually happened
by accident: There was a reason for even the oddest events. For
instance, one day, investors woke up to discover that they’d
bought shares in some company for $30.0001. Why? How was
it possible to pay ten-thousandths of a penny for anything? Easy:
High-frequency traders had asked for an order type that enabled
them to tack digits on the right side of the decimal, so that they
might jump the queue in front of people trying to pay $30.00.
The reason for change was seldom explained; change just hap-
pened. “The fact that it is such an opaque industry should be
alarming,” Brad said. “The fact that the people who make the
most money want the least clarity possible — that should be
alarming, too.”
Everything he had done with his new exchange was aimed
at making it more transparent, and forcing Wall Street to fol-
low. The sixteen investors understood IEX’s basic commercial
strategy: to open as a private stock market and convert to a pub-
lic exchange once their trading volume justified incurring the
millions of dollars in regulatory fees they would have to pay.
Although technically a dark pool, IEX had done something no
Wall Street dark pool had ever done: It had published its rules.
Investors could see, for the first time, what order types were
allowed on the exchange, and if any traders had been given spe-
cial access. IEX, as a dark pool, would thus try to set a new
standard of transparency — and perhaps shame others into fol-
lowing its example. Or perhaps not. “I would have thought one
dark pool would have come forward after us and published their
own rules,” Brad now told the investors. “ Someone must have
nothing to hide. My prediction was six or seven out of the forty-
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four would have done it. None. Zero. There are now forty-five
markets. On forty-four of them no one has any idea how they
trade. Has it not dawned on anyone that it might actually be a
good idea to tell people how the market works? People can look
back on the financial crisis and say, ‘How can you give a mort-
gage loan with no documentation? It’s preposterous.’ But banks
did it. And now trillions of dollars of trades are being executed
on markets where no one has any idea of how it works, because
there is no documentation. Does that sound familiar?”
Now he explained just how badly the market wanted to
remain in the shadows — and just how badly the people at the
heart of it wanted IEX to fail. Even before IEX opened, brokers
from the big Wall Street banks went to work trying to under-
mine them. One investor called to inform Brad that a repre-
sentative of Bank of America had just told him that IEX was
owned by high-frequency trading firms. On the morning IEX
opened, a manager at an investment firm called ING sent out
a mass email that looked as if it had been written on her behalf
by someone inside one of the big Wall Street banks: “With the
pending launch of IEX, we request that all ING Equity Trading
executions be excluded from executing on the IEX venue. . . .
I am still challenged by the conflict of interest inherent in their
business model. As a result I request to opt out of trading with
the IEX venue.”
The employees of IEX had risked their careers to attack the
conflicts of interest in the stock market. They had refused the
easy capital from the big Wall Street banks — to avoid conflicts
of interest. To avoid conflicts of interest, the investors who had
backed IEX had structured their investments so that they them-
selves did not personally profit from sending trades onto the
exchange: Profits from their investment flowed through to the
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people whose money they managed. These investors had further
insisted on having a stake of less than 5 percent in the exchange,
to avoid having even the appearance of control over it. Before
IEX launched, Brad had rebuffed an overture from Interconti-
nentalExchange (known as ICE), the new owners of the New
York Stock Exchange, to buy IEX for hundreds of millions of
dollars — and walked away from the chance to get rich quick.
To align their interests with the broader market’s, IEX planned
to lower their fees as their volumes rose — for everyone who
used the exchange. And on the day IEX opened for trading, this
manager at ING — who had earlier refused to meet with them
so that they might explain the exchange to her — was spreading
a rumor that IEX had a conflict of interest.’
But then all sorts of bizarre behavior had attended IEX’s
arrival in the U.S. stock market. Ronan had gone to a private
trade conference — no media, lots of Wall Street big shots. It was
the first time he had been invited to the exclusive event, and he
intended to lie low. He was outside in the hallway on his way to
the bathroom when someone said, “You know, they’re in there
talking about IEX.” Ronan returned to the conference room and
listened to the heads of several big public U.S. stock exchanges
on a panel. All agreed that IEX would only contribute to the
biggest problem in the U.S. stock market: its fragmentation.
The market already had thirteen public exchanges and forty-
four private ones: Who needed another? When it came time for
audience participation, Ronan found a microphone. “Hi, I’m
* ING, oddly enough, managed IEX’s then thirty-person 401(k) plan. Seeing this, John
Schwall returned to his side career in private investigation. After some digging, he
developed the opinion that any money manager who arbitrarily denied his clients access
to markets might have violated his fiduciary responsibility. On those grounds, Schwall
pulled the company’s 401(k) from ING.
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Ronan, and I think I went to go take a piss at the wrong time,”
he said, and then gave a little speech. “Were not like you guys,”
he concluded. “Or anyone else in the market. We’re an army
of one.” He thought he was being calm and measured, but the
crowd, by its standards, went wild — which is to say they actually
clapped. “Jesus, I thought you were about to throw a punch,”
some guy said afterward.
The stock exchanges didn’t like IEX for obvious reasons, the
big Wall Street banks for less obvious ones. But the more the
big banks sensed that Brad was being regarded by big inves-
tors as an arbiter of Wall Street behavior, the more carefully
they confronted him. Instead of voicing their own objections
to him directly, they would voice objections they claimed to
have heard from other big banks. The guy from Deutsche Bank
would say that the guy from Citigroup was upset that IEX was
telling investors how to tell the banks to route to IEX — that sort
of thing. “When I visited, they were all cordial,” said Brad. “It
made me feel that the plan was to starve us out.” But without
seeming to do so. The day before they’d opened for trading, a
guy from Bank of America called Brad and said, Hey, buddy,
what’s going on? I’d appreciate it if you’d say we’re being supportive.
Bank of America had been the first to receive the documents
they needed to connect to the exchange and, on opening day,
were still dragging their feet in establishing a connection. Brad
declined to help Bank of America out of its jam. “Shame is a
huge tactic we have to deploy,” he said.
Nine weeks after IEX launched, it was already pretty clear
that the banks were not following their customers’ instructions
to send their orders to the new exchange. A few of the investors
in the room knew this; the rest now learned. “When we told
them we wanted to route to IEX,” one said, “they said, Why
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215
would you want that? We can’t do that!’ The phrase ‘squealing
pigs’ comes to mind.” After the first six weeks of IEX’s life, UBS,
the big Swiss bank, inadvertently disclosed to one big investor
that it hadn’t routed a single order onto IEX — despite explicit
instructions from the investor to do so. Another big mutual fund
manager estimated that, when he told the big banks to route to
IEX, they had followed his instructions “at most ten percent of
the time.” A fourth investor was told, by three different banks,
that they didn’t want to connect to IEX because they didn’t
want to pay the $300-a-month connection fee.
Of all the banks that dragged their feet after their customers
asked them to send their stock market orders to IEX, Goldman
Sachs had offered the best excuse: They were afraid to tell their
computer system to do anything it hadn’t done before. In August
2013, the Goldman automated trading system generated a bunch
of crazy and embarrassing trades that lost Goldman hundreds
of millions of dollars (until the public exchanges agreed, amaz-
ingly, to cancel them). Goldman wanted to avoid giving new
instructions to its trading machines until it figured out why
they had ceased to follow the old ones. There was something
about the way Goldman had treated Brad when he visited their
offices — listening to what he had to say, bouncing him up the
chain of command rather than out the door — that led him to
believe their excuse. He sensed that they were taking him seri-
ously. After his first meeting with their stock market people, for
instance, Goldman’s analysts had told the firm’s clients that they
should be more wary of investing in Nasdaq Inc.
The other banks — Morgan Stanley and J.P. Morgan were
the exceptions — were mostly passive-aggressive, but there were
occasions when they became simply aggressive. Employees of
Credit Suisse spread rumors that IEX wasn’t actually mdepen-
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dent but owned by the Royal Bank of Canada — and so just a tool
of a big bank. One night, in a Manhattan bar, an IEX employee
bumped into a senior manager at Credit Suisse. “After you guys
fail, come to me and I’ll give you a job,” he said. “Wait, no,
everyone hates your fucking guts, so I won’t.” In the middle of
their first day of trading, one of IEX’s employees got a call from
a senior executive of Bank of America, who said that one of his
colleagues had “ties to the Irish Mafia,” and “you don’t want to
piss those guys off.” The IEX employee went to Brad, who just
said, “Tie’s full of shit.” The IEX employee was less sure, and
followed the call with a text.
IEX employee: Should I be concerned?
Bank of America employee: Yes.
IEX employee: Are you serious?
Bank of America employee: Jk [Just kidding].
IEX employee: Haven’t noticed any Irish guys following me.
Bank of America employee: Be careful next time you get in
your car.
IEX employee: Good thing I don’t own a car.
Bank of America employee: Well, maybe your gf’s car.
Brad also heard what the big Wall Street banks were already
saying to investors to dissuade them from sending orders to
IEX: It’s too slow. For years, the banks had been selling the speed
and aggression of their trading algos, along with the idea that,
for an investor, slower always meant worse. They seemed to have
persuaded themselves that the new speed of the markets actu-
ally helped their clients. They’d even dreamed up a technical-
sounding name for an absence of speed: “duration risk.” (“If you
make it sound official, people will believe that it’s something you
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really need to care about,” Brad explained.) The 350-microsecond
delay IEX had introduced to foil the stock market predator was
roughly one-thousandth of the blink of an eye. But investors for
years had been led to believe that one-thousandth of the blink of
an eye might matter to them, and that it was extremely impor-
tant for their orders to move as fast and aggressively as possible.
Guerrilla! Raider! This emphasis on speed was absurd: No matter
how fast the investor moved, he would never outrun the high-
frequency traders. Speeding up his stock market order merely
reduced the time it took for him to arrive in HFT’s various
traps. “But how do you prove that a millisecond is irrelevant?”
Brad asked.
He threw the problem to the Puzzle Masters. The team had
expanded to include Larry Yu, whom Brad thought of as the
guy with the box of Rubik’s cubes under his desk. (The standard
3x3-inch cube he could solve in under thirty seconds, and so he
kept it oiled with WD-40 to make it spin faster. His cube box
held more challenging ones: a 4x4-incher, a 5x5-incher, a giant
irregularly shaped one, and so on.) Yu generated two charts,
which Brad projected onto the screen for the investors.
To see anything in the stock market, you have to stop try-
ing to see it with your eyes and instead attempt to imagine it
as it might appear to a computer, if a computer had eyes. The
first chart showed the investors how trading on all public U.S.
stock exchanges in the most actively traded stock of a single
company (Bank of America Corp) appeared to the human eye
over a period of ten minutes, in one-second increments. The
activity appears constant, even frantic. In virtually every second,
something occurs: a trade or, more commonly, a new buy or sell
order. The second chart illustrated the same activity on all pub-
lic U.S. stock exchanges as it appeared to a computer, over the
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course of a single second, in millisecond increments. All the mar-
ket activity within a single second was so concentrated — within
a mere 1.78 milliseconds — that on the graph it resembled an
obelisk rising from a desert. In 98.22 percent of all milliseconds,
nothing at all happened in the U.S. stock market. To a computer,
the market in even the world’s most actively traded stock was an
uneventful, almost sleepy place. “Yes, your eyeballs think the
markets are going fast,” Brad said. “They aren’t really going that
fast.” The likelihood an investor would miss out on something
important in a third of a millisecond was close to zero, even in
the world’s most actively traded stock. “I knew it was bullshit to
worry about milliseconds,” said Brad, “because if milliseconds
were relevant, every investor would be in New Jersey.”
“What’s the spike represent?” asked one of the investors,
pointing to the obelisk.
“That’s one of your orders touching down,” said Brad.
A few investors shifted in their seats. It was growing clear to
them, if it wasn’t already so, that, if the stock market was the
party, they were the punch bowl. They were unlikely to miss
any action as the result of a delay of one-third of a millisecond.
They were the reason for all the action! “Every time a trade
happens at the exchange, it creates a signal,” said Brad. “In the
fifty milliseconds running up to it — total silence. Then there is
an event. Then there is this massive reaction. Then a reaction to
that reaction. The HFT algos on the other side are predicting
what you’ll do next based on what you just did.” The activity
peaked roughly 350 microseconds after an investor’s order trig-
gered the feeding frenzy, or the time it took for HFT to send
its orders from the stock exchange on which the investor had
touched down to all of the others. “Your eye will never pick up
what is really happening,” said Brad. “You don’t see shit. Even
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if you’re a fucking cyborg you don’t see it. But if there was no
value to reacting, why would anyone react at all?” The arrival of
the prey awakened the predator, who deployed his strategies —
rebate arbitrage, latency arbitrage, slow market arbitrage. Brad
didn’t need to dwell on these; he’d already walked each of the
investors through his earlier discoveries. It was his new findings
that he wanted them to focus on.*
On IEX’s opening day — when it had traded just half a million
shares — the flow of orders through its computers had been too
rapid for the human eye to make sense of it. Brad had spent the
first week or so glued to his terminal, trying to see whatever he
could see. Even that first week, he was trying to make sense of
lines scrolling down his computer screen at a rate of fifty per sec-
ond. It felt like speed-reading War and Peace in under a minute.
All he could see was that a shocking number of the orders being
sent by the Wall Street banks to IEX came in small 100-share
lots. The HFT guys used 100-share lots as bait on the exchanges,
to tease information out of the market while taking as little risk
as possible. But these weren’t HFT orders; these were from the
big banks. At the end of one day, he asked for a count of one
bank’s orders: 87 percent of them were in these tiny 100-share
lots. Why?
The week after Brad had quit his job at the Royal Bank of
Canada, his doctor noted that his blood pressure had collapsed
to virtually normal levels, and he’d cut his medication in half.
Now, in response to this new situation he couldn’t make sense
* Sixty percent of the time that this feeding frenzy occurs on a public stock exchange,
no trade is recorded. The frenzy comes in response to a trade that has occurred in some
dark pool. The dark pools are not required to report their trades in real time; and so, on
the official tape, the frenzy appears unprovoked. It isn’t.
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of, Brad had migraines, and his blood pressure was again spik-
ing. “I’m straining to see patterns,” he said. “The patterns are
being shown to me, but my eyes can’t pick them up.”
One afternoon, an IEX employee named Josh Blackburn
overheard Brad mention his problem. Josh was quiet — not just
reserved, but intensely so — and didn’t say anything at first. But
he thought he knew how to solve the problem. With pictures.
Josh, like Zoran, traced his career back to September 11,
2001. He’d just started college when a friend messaged him to
turn on the TV, and he’d watched the Twin Towers collapse.
“When that happened it was kind of a what can I do moment?” A
couple of months later, he’d gone to the local air force recruit-
ing center and attempted to enlist. They’d told him to wait
until the end of his freshman year. At the end of the school year
he’d returned. The air force sent him to Qatar, where a colonel
figured out that he had a special talent for writing computer
code; one thing led to another, and two years later he was in
Baghdad. There he created a system for getting messages to
all remote units, and another system for creating a Google-
like map, before the existence of Google maps. From Baghdad
he’d gone to Afghanistan, where he wound up being in charge
of taking the data from all the branches of the U.S. military
across all battlefields and turning it into a single picture the
generals could use to make decisions. “It told them everything
that was going on, real-time, on a twenty-foot wall map,” Josh
said. “You could see trends. You could see origins of rocket
attacks. You could see patterns in when they occurred — the
attacks on [U.S. Army base] Camp Victory would come after
afternoon prayer. You could see what the projections were [of
where and when the attacks might occur] and how they com-
pared to where attacks actually happened.” The trick was not
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simply to write the code that turned information into pictures
but to find the best pictures to draw — shapes and colors that
led the mind to meaning. “Once you got all that stuff together
and showed it in the best way possible, you could find pat-
terns,” Josh said.
The job was hard to do, but, as it turned out, harder to stop
doing. When his first tour of duty was up, Josh reenlisted, and
when that tour ended, he re-upped again. When his third tour
was over, he saw the war winding down and his usefulness
diminish. “You find it very difficult to come home from,” said
Josh. “Because you see the impact of your work. After that,
I couldn’t find any passion in anything I did, any meaning.”
Coming home, he looked for a place to deploy his skill — and
a friend in finance told him about an opening in a new high-
frequency trading firm. “In the war, you’re trying to use the
picture you create to take advantage of the enemy,” said Josh.
“In this case, you’re trying to take advantage of the market.” He
worked for the HFT firm for six weeks before it failed, but he
found the job unsatisfying.
He’d come to IEX in the usual way: John Schwall had found
him while trolling on Linkedln and asked him to come for an
interview. At that point, Josh was being inundated with offers
from other high-frequency trading firms. “There was a lot of
‘we are elite,’ ” he said. “They kept hitting the elite thing.” He
didn’t care all that much about being elite; he just wanted his
work to mean something. “I came in for an interview on Fri-
day. Saturday they made me an offer. Brad said, we’re going to
change the way things work. But I didn’t really know what Brad
was talking about.” Since joining, he’d been quiet and had put
himself where he liked to be, in the background. “I just try to
take in what people are saying, and listen to what everyone is
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complaining about,” he said. “I wish this or I wish that, and then
bring it together and find the solution.”
Brad knew little of Josh’s past — only that whatever Josh had
done for the U.S. military sounded like the sort of thing he
couldn’t talk about. “All I knew was that he was in a trailer in
Afghanistan, working with generals,” said Brad. “When I tell
him my problem — that I couldn’t see the data — he just says, ‘Hit
Refresh.’”
Quietly, Josh had gone off and created for Brad pictures of
the activity on IEX. Brad hit Refresh; the screen was now orga-
nized in different shapes and colors. The strange 100-lot trades
were suddenly bunched together and highlighted in useful ways:
He could see patterns. And in the patterns he could see preda-
tory activity neither he nor the investors had yet imagined.
These new pictures showed him how the big Wall Street banks
typically handled investors’ stock market orders. Here’s how it
worked: Say you are a big investor — a mutual fund or a pension
fund — and you have decided to make a big investment in Procter
& Gamble. You are acting on behalf of a lot of ordinary Ameri-
cans who have given you their savings to manage. You call some
broker — Bank of America, say — and tell them you’d like to buy
100,000 shares of Procter & Gamble. P&G’s shares are trading at,
say, 82.95—82.97, with 1,000 shares listed on each side. You tell
the big Wall Street bank you are willing to pay up to, say, $82.97
a share. From that point on, you basically have no clue how your
order — and the information it contains — is treated. Now Brad
saw: The first thing the broker did was to ping IEX with an order
to buy 100 shares, to see if IEX had a seller. This made total sense:
You didn’t want to reveal you had a big buyer until you found a
seller. What made a lot less sense was what many of the brokers
did after they discovered the seller. They avoided him.
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Say, for example, that IEX actually had a seller waiting on
it — a seller of 100,000 shares at $82.96. Instead of coming in
and trying to buy a much bigger chunk of P&G, the big bank
just kept pinging IEX with tiny 100-share orders — or the bank
vanished entirely. If the bank had simply sent IEX an order to
buy 100,000 shares of P&G at $82.97, the investor would have
purchased all the shares he wanted without driving up the price.
Instead, the bank had pinged away and — by revealing its insis-
tent, noisy demand — goosed up the price of P&G’s stock, at the
expense of the investor whose interests the bank was meant to
represent. Adding to the injury, the bank typically wound up
with only a fraction of the stock its customer wanted to buy. “It
opened up this whole new realm of activity that was crazy to
me,” Brad told his audience. It was as if the big Wall Street banks
were looking to see if IEX had a big seller to avoid trading with
him. “1 thought, Why the hell would anyone do this? All you
do is increase the chances that an HFT will pick up your signal.”
They didn’t all behave this way: A couple of the big banks
followed up their 100-share orders by forking over the meat of
the buy order, and executed the trade their customer had asked
them to execute. (The Royal Bank of Canada was by far the
best behaved.) But, in general, the big Wall Street banks who
had connected to IEX — a group that in the first week of trading
excluded Bank of America and Goldman Sachs — connected dis-
ingenuously. It was as if they wished to appear to be interacting
with the entire stock market, while actually they were trying to
prevent any trades from happening outside their own dark pools.
Brad now explained to the investors, who were of course pay-
ing the price for this behavior, the reasons that the banks behaved
as they did. The most obvious was to maximize the chance of
executing the stock market orders given to them by investors in
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their own dark pools. The less honestly a bank looked for P&G
stock outside of its own dark pool, the less likely it was to find it.
This evasiveness explained the banks’ incredible ability to find,
eventually, the other side of any trade inside their own dark
pools. A bank that controlled less than 10 percent of all U.S.
stock market orders was somehow able to satisfy more than half
of its customers’ orders without ever leaving its own dark pool.
Collectively, the banks had managed to move 38 percent of the
entire U.S. stock market now traded inside their dark pools —
and this is how they had done it. “It’s a facade that the market is
interconnected,” said Brad.
The big Wall Street banks wanted to trade in their own dark
pools not only because they made more money — on top of their
commissions — by selling the right to HFT to exploit orders
inside their dark pools. They wanted to trade their orders inside
their dark pools to boost the volumes in those pools, for appear-
ances’ sake. The statistics used to measure the performance of
the dark pools, as well as the performance of the public stock
exchanges, were more than a little screwy. A stock market was
judged by the volume of trading that occurred on it, and the
nature of that volume. It was widely believed, for example, that
the bigger the average trade size on an exchange, the better the
market was for an investor. (By requiring fewer trades to com-
plete his purchase or sale, the exchange reduced the likelihood
of revealing an investor’s intentions to high-frequency traders.)
Every dark pool and every stock exchange found ways to cook
its own flattering statistics; the art of torturing data may never
have been so finely practiced. For example, to show that they
were capable of hosting big trades, the exchanges published the
number of “block” trades of more than 10,000 shares they facil-
itated. The New York Stock Exchange sent IEX a record of
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26 small trades it had made after IEX had routed an order to
it — and then published the result on the ticker tape as a single
15,000-share block. The dark pools were even worse, as no one
but the banks that ran them had a clear view of what happened
inside them. The banks all published their own self-generated
stats on their own dark pools: Every bank ranked itself #1. “It’s
an entire industry that overglorifies data, because data is so easy
to game, and the true data is so hard to obtain,” said Brad.
The banks did not merely manipulate the relevant statistics in
their own dark pools; they often sought to undermine the stats
of their competitors. That was another reason the banks were
sending IEX orders in tiny 100-share lots: to lower the average
trade size in a market that competed with the banks’ dark pools.
A lower average trade size made IEX’s stats look bad — as if IEX
were heavily populated by high-frequency traders. “When the
customer goes to his broker and says, ‘What the hell happened?
Why am I getting all these hundred-share fills?,’ his broker could
easily say, ‘Well, I put the order on IEX,’ ” said Brad. The strat-
egy cost their customers money, and the opportunity to buy and
sell shares, but the customers wouldn’t know about it: All they
would see was IEX’s average trade size falling.
Soon after it opened for trading, IEX published its own sta-
tistics — to describe, in a general way, what was happening in its
market. “Since everyone is behaving in a particular way, you
can’t see if anyone is behaving particularly badly,” said Brad.
Now you could see. Despite the best efforts of Wall Street banks,
the average size of IEX’s trades was by far the biggest of any
stock exchange, public or private. More importantly, the trading
that occurred was more random, unlinked to activity elsewhere
in the stock market: For instance, the percentage of trades on
IEX that followed the change in the price of some stock was
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half that of the other exchanges. (Investors were being picked
off — as West Chester, Pennsylvania, money manager Rich
Gates had been picked off — on exchanges that failed to move
their standing orders quickly enough to keep up when stock
prices changed.) Trades on IEX were also four times more likely
than those elsewhere to trade at the midpoint between the cur-
rent market bid and offer — which is to say, the price that most
would agree was fair. Despite the reluctance of the big Wall
Street banks to send them orders, the new exchange was already
making the dark pools and public exchanges look bad, even by
their own screwed-up standards.*
Brad’s biggest weakness, as a strategist, was his inability to
imagine just how badly others might behave. He had expected
that the big banks would resist sending orders to IEX. He hadn’t
imagined they would use their customers’ stock market orders
to actively try at their customers’ expense to sabotage an exchange
created to help their customers. “You want to create a system
where behaving correctly would be rewarded,” he concluded.
“And the system has been doing the opposite. It’s rational for a
broker to behave badly.”
The bad behavior played right into the hands of high-
frequency traders in the most extraordinary ways. One day while
watching the pictures Josh Blackburn had created for him. Brad
saw a bank machine-gun IEX with 100-share lots and drive up
a stock price 5 cents inside of 232 milliseconds. IEX’s delay —
one-third of a millisecond — was of little use in disguising an
* The Financial Industry Regulatory Authority (FINRA) publishes its own odd rank-
ing of the public and private stock markets, based on how well they avoid breaking the
law, presumably inadvertently, by trading outside the National Best Bid and Offer. In its
first two months of trading, IEX ranked #1 on FINRA’s list.
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investor’s stock market order if a broker insisted on broadcasting
a big order he controlled over a far longer period: HFT picked
up the signal and was getting out in front of it. Wondering if
the broker was spreading news of his buy order elsewhere, Brad
turned his attention to the consolidated tape of all the trades
that occurred in the U.S. stock market. “I just wondered: Is this
broker peppering the whole Street, or is it just us?” he told the
room full of investors. “What we found blew our minds.”
For each trade on IEX, he’d spotted a nearly identical trade
that had occurred at nearly the same time in some other mar-
ket. “I noticed the odd trade sizes,” he said. He’d see a trade on
IEX for 131 shares of, say, Procter & Gamble, and then he’d see,
in some other market, exactly the same trade — 131 shares of
Procter & Gamble — within a few milliseconds, but at a slightly
different price. It happened over and over again. He also noticed
that, in each case, on one side of the trade was a broker who had
rented out his pipes to a high-frequency trader.
Up till that point, most of the predation they had uncovered
occurred when stock prices moved. A stock went up or down;
the high-frequency guys found out before everyone else and
took advantage of them. Roughly two-thirds of all stock market
trades took place without moving the price of the stock— the
trade happened at the seller’s offering price, or the buyer’s bid-
ding price, or in between; afterwards, the bid and offering price
remained the same as they had been before. What Brad now
saw was how HFT, with the help of the banks, might exploit
investors even when the stock price was stable. Say the market
for Procter & Gamble’s shares was 80.50-80.52, and the quote
was stable — the price wasn’t about to change. The National Best
Bid was $80.50, and the National Best Offer was $80.52, and the
stock was just sitting there. A seller of 10,000 Procter & Gamble
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shares appeared on IEX. IEX tried to price the orders that rested
on it at the midpoint (the fair price), and so the 10,000 shares
were being offered at $80.51. Some high-frequency trader would
come into IEX — it was always a high-frequency trader — and
chip away at the order: 131 shares here, 189 shares there. But else-
where in the market, the same HFT was selling the shares — 131
shares here, 189 shares there— at $80.52. On the surface, HFT
was performing a useful function, building a bridge between
buyer and seller. But the bridge was itself absurd. Why didn’t
the broker who controlled the buy order simply come to IEX on
behalf of his customer and buy, more cheaply, the shares offered?
Back when Rich Gates conducted his experiments, he had
managed to get himself robbed inside Wall Street’s dark pools,
but only after he had changed the price of the stock (because the
dark pools were so slow to move the price of his order resting
inside of them). These trades that Brad was now noticing had
happened without the market moving at all. He knew exactly
why they were happening: The Wall Street banks were fail-
ing to send their customers’ orders to the rest of the market-
place. An investor had given a Wall Street bank an order, say,
to buy 10,000 shares of P&G. The bank had sent it to its dark
pool with instructions for the order to stay there, aggressively
priced, at $80.52. The bank was boosting its dark pool stats —
and also charging some HFT a fee rather than paying a fee to
another exchange — but it was also ignoring whatever else was
happening in the market. In a functional market, the inves-
tors would simply have met in the middle and traded with each
other at a price of $80.51. The price of the stock needn’t have
moved a penny. The unnecessary price movement — caused by
the screwed-up stock market— also played into HFT’s hands.
Because high-frequency traders were always the first to detect
any stock price movements, they were able to exploit, with other
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strategies, ordinary investors’ ignorance of the fact that the mar-
ket price had changed. The original false note struck by the big
Wall Street bank — the act of avoiding making trades outside of
its own dark pool— became the prelude to a symphony of scalp-
ing.* “We’re calling this ‘dark pool arbitrage,’ ” said Brad.
IEX had built an exchange to eliminate the possibility of
predatory trading — to prevent investors from being treated as
prey. In the first two months of its existence, IEX had seen no
activity from high-frequency traders except this. It was aston-
ishing, when you stopped to think about it, how aggressively
capitalism protected its financial middleman, even when he was
totally unnecessary. Almost magically, the banks had generated
the need for financial intermediation — to compensate for their
own unwillingness to do the job honestly.
Brad opened the floor for questions. For the first few minutes,
the investors vied with each other to see who could best control
his anger and exhibit the sort of measured behavior investors are
famous for.
“Do you think of HFT differently than you did before you
opened?” asked one.
That question might have been better answered by Ronan,
who had just returned from a tour of the big HFT firms, and
now leaned against a wall on the side of the room. Brad had asked
Ronan to explain to the investors the technical end of things —
* The reader might question the characterization of such small-time skimming as scalp-
ing. But a penny here, a penny there adds up in the most extraordinary ways in the
U.S. stock market. At IEX, the Puzzle Masters made a quick-and-dirty calculation of
the likely profits made annually by HFT from dark pool arbitrage. They added up all
its instances over a fifteen-day period, then came up with a number: The haul for HFT
from the U.S. stock market alone came to more than a billion dollars a year. And this
was just a single trading strategy. “They’ve been in business for ten weeks and they’ve
now found four of these strategies,” said one big investor of IEX. “Who knows how
many more they’ll find?” A billion here, a billion there: It adds up.
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how IEX had created its 350-microsecond delay, the magic shoe-
box, and so on — and to relate the details of his tour. He’d done
it. But on the subject of HFT he held himself back. To speak his
mind, Ronan needed to feel like himself, which, imprisoned in
a gray suit and addressing a semiformal audience, he clearly did
not. Put another way: It was just extremely difficult for Ronan
to say what he felt without using the word “fuck.” Watching
him string together sentences without profanity was like watch-
ing someone try to swim across a river without using his arms or
his legs. Curiously, he later admitted, he wasn’t worried that the
audience would be offended by bad language. “It was because
some of them want to be the alpha male cursing in the room,”
he said. “When I say ‘fuck,’ they think I’m stealing the show —
so when I’m in front of a group I go as straight as I can.”
“I hate them a lot less than before we started,” said Brad.
“This is not their fault. I think most of them have just rational-
ized that the market is creating the inefficiencies and they are
just capitalizing on them. Really, it’s brilliant what they have
done within the bounds of the regulation. They are much less of
a villain than I thought. The system has let down the investor.”
A forgiving sentiment. But at that moment the investors in
the conference room did not seem in a forgiving mood. “It’s still
shocking to me to see how the banks are colluding against us,”
one of the investors later said. “It shows everyone is a bad actor.
And then when you add in that you ask them to route to IEX
and they refuse, it’s even worse. Even though I had heard some
of it before, I was still incensed. If that was the first time I was
hearing it, I think I’d have gone bonkers.”
An investor raised his hand and motioned to some numbers
Brad had scribbled on a whiteboard to illustrate how a particular
bank had enabled dark pool arbitrage.
“Who is that?” he asked, and not calmly.
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An uneasy look crossed Brad’s face. He was now hearing that
question more and more. Just that morning, an outraged inves-
tor listening to a dry run of his presentation had stopped him to
ask: “Which bank is the worst?” “I can’t tell you,” he said, and
explained that the agreements the big Wall Street banks signed
with IEX forbade IEX from speaking about any bank without
its permission.
“Do you know how frustrating it is to sit here and hear this
and not know who that broker is?” said another investor.
It wasn’t easy being Brad Katsuyama — to try to effect some
practical change without a great deal of fuss, when the change in
question was, when you got right down to it, a radical overhaul
of a social order. Brad was not by nature a radical. He was simply
in possession of radical truths.
“What we want to do is highlight the good brokers,” said
Brad. “We need the brokers who are doing the right thing to get
rewarded.” That was the only way around the problem. Brad had
asked for the banks’ permission to highlight the virtue of the ones
that behaved relatively well, and they had granted it. “Speaking
about someone in a positive light does not violate the terms of not
speaking about someone in a negative light,” he said.
The audience considered this.
“How many good brokers are there?” asked an investor at
length.
“Ten,” said Brad. (IEX had dealings with ninety-four.) The
ten included the Royal Bank of Canada, Sanford Bernstein, and
a bunch of even smaller outfits. “Three are meaningful,” he
added. Morgan Stanley, J.P. Morgan, and Goldman Sachs.
“Why would any broker behave well?”
“The long-term benefit is that when the shit hits the fan, it
will quickly become clear who made good decisions and who
made bad decisions,” said Brad.
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He wondered, often, what it would look like if and when
the shit in question hit the fan: The stock market at bottom was
rigged. The icon of global capitalism was a fraud. How would
enterprising politicians and plaintiffs’ lawyers and state attorneys
general respond to that news? The thought of it actually didn’t
give him all that much pleasure. Really, he just wanted to fix
the problem. At some level, he still didn’t understand why Wall
Street banks needed to make his task so difficult.
“Is there a concern from you that the publicity will create
even more hostility?” asked another. He wanted to know if tell-
ing the world who the good brokers were would make the bad
ones worse.
“The bad brokers can’t try harder at being bad,” said Brad.
“Some of these brokers are doing everything they can not to do
what the client wants them to do.”
An investor wanted to return to the scribbled numbers that
illustrated how one particular bank had enabled dark pool arbi-
trage. “So what do these guys say when you show them that?
“Some of them say, ‘You’re one hundred percent right,”’
said Brad. “ ‘This shit happens.’ One even said, ‘We used to sit
around all the time talking about how to fuck up other people’s
dark pools.’ Some of them say, ‘I have no idea what you’re talk-
ing about. We have heuristic data bullshit and other mumbo
jumbo to determine our routing.’ ”
“That’s a technical term — ‘heuristic data bullshit and other
mumbo jumbo’?” an investor asked. A few guys laughed.
Technology had collided with Wall Street in a peculiar way.
It had been used, as it should have been used, to increase effi-
ciency. But it had also been used to introduce a peculiar sort
of market inefficiency. This new inefficiency was not like the
inefficiencies that financial markets can easily correct. After a
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big buyer enters the market and drives up the price of Brent
crude oil, for example, it’s healthy and good when speculators
jump in and drive up the price of North Texas crude, too. It’s
healthy and good when traders see the relationship between the
price of crude oil and the price of oil company stocks, and drive
these stocks higher. It’s even healthy and good when some clever
high-frequency trader divines a necessary statistical relationship
between the share prices of Chevron and Exxon, and responds
when it gets out of whack. It was neither healthy nor good when
public stock exchanges introduced order types and speed advan-
tages that high-frequency traders could use to exploit everyone
else. This sort of inefficiency didn’t vanish the moment it was
spotted and acted upon. It was like a broken slot machine in the
casino that pays off every time. It would keep paying off until
someone said something about it; but no one who played the
slot machine had any interest in pointing out that it was broken.
Some large amount of what Wall Street had done with tech-
nology had been done simply so that someone inside the financial
markets would know something that the outside world did not.
The same system that once gave us subprime mortgage collater-
alized debt obligations no investor could possibly truly under-
stand now gave us stock market trades that occurred at fractions
of a penny at unsafe speeds using order types that no investor
could possibly truly understand. That is why Brad Katsuyama’s
most distinctive trait — his desire to explain things not so he
would be understood but so that others would understand — was
so seditious. He attacked the newly automated financial system
at its core: the money it made from its incomprehensibility.
Another investor, silent till that point, now raised his hand.
“It seems like there’s a first mover risk for someone to behave
the right way,” he said. He was right: Even the banks that were
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behaving relatively well weren’t behaving all that well. A big
Wall Street bank that gave IEX an honest shot to execute its
customers’ orders would suffer a collapse in its dark pool trad-
ing, and in its profits. The bad banks would pounce on the good
bank and argue that, because its dark pool was worse than all the
others, it shouldn’t be given the orders in the first place. That,
Brad told the investors, had been maybe his biggest concern.
Would any big Wall Street bank have the ability to see a few
years down the road, and summon the nerve to go first? Then
he clicked on a slide. On top it read: December 19, 2013.
YOU COULD NEVER say for sure exactly what was going on inside
one of the big Wall Street banks, but it was a mistake to think of
a bank as a coherent entity. They were fractious, and intensely
political. Most everyone might be thinking mainly about his
year-end bonus, but that didn’t mean there wasn’t one person
who wasn’t, and it certainly didn’t mean that everyone inside a
big bank shared the same incentives. A dollar in one guy’s pocket
was, in some places, a dollar out of another’s. For instance, the
guys in the prop group who traded against the firm’s custom-
ers in the dark pool would naturally feel a different concern for
those customers than the guy whose job it was to sell them stuff
would — if for no other reason than that it is harder to rip off a
person when you actually need to see him, face to face. That’s
why the banks kept the prop traders on different floors from the
salespeople, often in entirely different buildings. It wasn’t simply
to please the regulators; all involved would prefer that there be
no conversation between the two groups. The customer guy was
better at his job — and had deniability — if he remained oblivi-
ous to whatever the prop guy was up to. The frantic stupidity
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of Wall Street’s stock order routers and algorithms was simply
an extension into the computer of the willful ignorance of its
salespeople.
Brad’s job, as he saw it, was to force the argument between
the salespeople and the prop people — and to arm the salespeople
with a really great argument, which included the distinct pos-
sibility that investors in the stock market were about to wake
up to what was being done to them, and go to war against the
people who were doing it. In most cases, he had no idea if he had
succeeded and, as a result, suspected he had not.
Right from the start, the view from inside Goldman Sachs had
been less cluttered than the view from inside the other big Wall
Street banks. Goldman was unlike the other banks; for instance,
the first thing the people he met at the other banks usually did
was tell him of the hostility all the other banks felt toward IEX,
and of the nefariousness of the other banks’ dark pools. Goldman
was aloof, and didn’t appear to care what its competitors were
saying or thinking about IEX. In their stock market trading and
perhaps in other departments as well, Goldman was undergoing
some kind of transition. In February 2013, its head of electronic
trading, Greg Tusar, had left to work for Getco, the big high-
frequency trading firm. The two partners then assigned to figure
out Goldman’s role in the global stock markets — Ron Morgan
and Brian Levine — were not high-frequency trading types.
They didn’t bear a great deal of responsibility for whatever the
high-frequency trading types had done before they took over.
Morgan worked in New York and was in charge of sales; Levine,
responsible for trading, worked in London. Both were apparently
worried about what they had found when they stepped into their
new positions. Brad knew this because, oddly, Ron Morgan had
called him. “He found us by talking to clients about what they
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wanted,” said Brad. A week after they first met, Morgan invited
Brad back to meet with a group of even more senior executives.
“That didn’t happen anywhere else,” Brad said. After he left, he
was told that the ensuing discussion had reached “the highest
levels of the firm.”
In taking over, Morgan and Levine had been tasked with
answering a big question posed by the people who ran Gold-
man Sachs: Why was Morgan Stanley growing so fast? Their
rival s market share was booming, while Goldman’s was stag-
nant. Levine and Morgan did what everyone on Wall Street
did when they wanted to find out what was going on inside a
rival bank: They invited some of its employees in for job inter-
views. The Morgan Stanley employees explained to them that
the firm was now trading 300 million shares a day — 30 percent
of the volume of the New York Stock Exchange — through what
it called “Speedway.” Speedway was a service Morgan Stanley
provided to high-frequency traders. Morgan Stanley built a
high-frequency trading infrastructure — co-location at various
exchanges, the fastest routes between them, a straight road into
the bank s dark pool and so on — and then turned around and
leased their facilities to the smaller HFT firms, which couldn’t
afford the up-front cost of building their own systems. Mor-
gan Stanley got credit for, and commissions from, everything
the HFT guys did inside Morgan Stanley’s pipes. The Morgan
Stanley employees angling for jobs at Goldman Sachs told the
Goldman executives that Speedway was now making Morgan
Stanley $500 million a year, and that it was growing. This raised
the obvious question for Goldman Sachs: Should we create our
own Speedway? Should we further embrace high-frequency
trading?
One of Goldman’s clients handed Ronnie Morgan a list of
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thirty-three big investors to whom he should speak before
making this decision. This client didn’t know if Morgan had
spoken to people beyond this list, but he confirmed for him-
self that Morgan had spoken to each of the thirty-three people
individually. At the same time, Morgan and Levine began to
ask some obvious questions about Goldman Sachs’s stock mar-
ket businesses. Could Goldman ever be as fast or as smart as
the more nimble high-frequency trading firms? Why, if Gold-
man only controlled 8 percent of all stock market orders, was it
able to trade more than a third of those orders in its own dark
pool? Given how little of the flow Goldman saw, what was the
likelihood that the best price for an investor’s order came from
some other Goldman customer? How did Wall Street dark pools
interact with each other and with the exchanges? How stable
was this increasingly complex financial market? Was it a good
thing that the U.S. stock market model had been exported to
other countries and other financial markets?
They already knew or could guess most of the answers; for
the questions still hanging, the investors pointed them toward
an unusually forthright and knowledgeable guy they knew and
trusted who was starting a new stock exchange: Brad Katsuyama.
What struck Brad about his visit to Goldman Sachs was not
only that Levine and Morgan were willing to spend time with
him, but that they took the ideas from their conversations to
their superiors. Levine seemed particularly concerned about the
stock market’s instability. “Unless there are some changes, there’s
going to be a massive crash,” he said, “a flash crash times ten.” In
conversation and in presentations, he impressed the point upon
Goldman’s top executives, and also asked, “Do you really need
the only differentiator in the market to be speed? Because that’s
what it seems to be.” It wasn’t all that hard for the people who
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ran Goldman Sachs to see the source of the problem, or to see
why no one inside the system cared to point it out. “There’s no
upside in it — that’s why no one ever steps out on it,” said Levine.
“And everyone’s got career risk. And no one is thinking that far
ahead. They are looking at the next paycheck.”
A long string of myopic decisions had created new risks in the
U.S. stock market. Its complexity was just one manifestation of
the problem, but in it, the Goldman partners both felt sure, lay
some future calamity. The sensational technical glitches weren’t
anomalies but symptoms. And a stock market calamity, Ron
Morgan and Brian Levine both thought, would end up being
blamed generally on the big Wall Street banks, and specifically
on Goldman Sachs. Goldman earned $7 billion a year from its
equity business; that business would be put at risk by any crisis.
But it was more than that. At forty-eight and forty-three,
respectively, Morgan and Levine were, by Wall Street standards,
old guys. Morgan had been made a Goldman partner back in
2004, Levine in 2006. Both confided to friends that IEX pre-
sented them with a choice, at what might be a pivotal financial
historical moment. An investor who knew Ron Morgan said,
“Ronnie’s saying to himself, ‘You work for twenty-five years in
the business, how often do you have a chance to make a differ-
ence?’ ” Brian Levine himself said, “I think it’s a business deci-
sion. I also think it’s a moral decision. I think this is the shot we
have. And I think Brad is the right guy. It’s the best odds we
have to fix the problem.”
BEFORE THEY OPENED their market, on October 25, 2013, the
thirty-two employees of IEX made private guesses as to how
many shares they’d trade their first day and in their first week.
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The median of the estimates came in at 159,500 shares the first
day and 2.5 million shares the first week. The lowest estimate
came from Matt Trudeau, the only one of them who had ever
built a new stock market from scratch: 2,500 shares for the first
day and 100,000 for the week. Of the ninety-four stock broker-
age firms in various stages of agreeing to connect to IEX, most
of them small outfits, only about fifteen were ready on the first
day. “Brokers are telling their clients they’re connected, but we
haven’t even gotten their paperwork,” said Brad. When asked
how big the exchange might be at the end of the first year, Brad
guessed, or perhaps hoped, that it would trade between 40 and
50 million shares a day.
To cover their running costs, they needed to trade about 50
million shares a day. If they failed to cover their running costs,
there was a question of how long they could last. “It’s binary,”
said Don Bollerman. “Either we are a resounding success or
we are a complete flop. We’re done in six to twelve months. In
twelve months I know whether I need to look for a job.” Brad
thought that their bid to create an example of a fair financial
market — and maybe change Wall Street’s culture — could take
longer and prove messier. He expected their first year to feel
more like nineteenth-century trench warfare than a twenty-
first-century drone strike. “We’re just collecting data,” he said.
“You cannot make a case without data. And you don’t have data
unless you have trades.” Even Brad agreed: “It’s over when we
run out of money.”
On the first day, they traded 568,524 shares. Most of the vol-
ume came from regional brokerage firms and Wall Street brokers
that had no dark pools — the Royal Bank of Canada and San-
ford Bernstein. Their first week, they traded a bit over 12 million
shares. Each week after that, they grew slightly, until, in the third
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week of December, they were trading roughly 50 million shares
each week. On Wednesday, December 18, they traded 11,827,232
shares. By then Goldman Sachs had connected to IEX, but its
orders were arriving on the new exchange in the same untrust-
ing spirit as those from the other big Wall Street banks: in tiny lot
sizes, resting for just a few milliseconds, then leaving.
The first different-looking stock market order sent by Gold-
man to IEX landed on December 19, 2013, at 3:09:42 p.m. 662
milliseconds, 361 microseconds, and 406 nanoseconds. Anyone
who had been in IEX’s one-room office when it arrived would
have known that something unusual was happening. The com-
puter screens jitterbugged as the information flowed into the
market in an entirely new way. One by one, the employees arose
from their chairs; a few minutes into the surge, all but Zoran
Perkov were on their feet. Then they began to shout.
“Were at fifteen million!” someone yelled, ten minutes into
the surge. In the previous 331 minutes they had traded roughly
5 million shares.
“Twenty million!”
“Fucking Goldman Sachs!”
“Thirty million!”
The enthusiasm was unpracticed, almost unnatural. It was as
if an oil well had gushed up through the floor during a meeting
of the chess club.
“We just passed AMEX,” shouted John Schwall, referring to
the American Stock Exchange. “We’re ahead of AMEX in mar-
ket share.”
“And we gave them a one-hundred-and-twenty-year head
start,” said Ronan, playing a little loose with history. Some-
one had given Ronan a $300 bottle of Champagne. He’d told
Schwall that it had cost only forty bucks, because Schwall didn’t
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241
want anyone inside IEX accepting gifts of more than forty bucks
from anyone outside of it. Now Ronan fished the contraband
from under his desk and found some paper cups.
Someone else put down a phone and said, “That was J.R
Morgan, asking, ‘What just happened?’ They say they may have
to do something.”
Don put down his phone. “That was Goldman. They say they
aren’t even big. They’re coming big tomorrow.”
“Forty million!”
At his desk Zoran sat calmly, watching traffic patterns. “Don’t
tell anyone, but we’re still bored,” he said. “This is nothing.”
Fifty-one minutes after Goldman Sachs had given them their
first honest shot at Wall Street customers’ stock market orders,
the U.S. stock market closed. Brad walked off the floor and into
a small office, enclosed by glass. He thought through what had
just happened. “We needed one person to buy in and say, ‘You’re
right,’ ” he said. “It means that Goldman Sachs agrees with us.”
Then he thought some more. Goldman Sachs wasn’t a single
entity; it was a bunch of people who didn’t always agree with
each other. Two of these people had been given a new authority,
and they had used it to take a different, longer-term approach
than anyone imagined Goldman Sachs was capable of. These
two people made all the difference. “I got lucky Brian is Brian
and Ronnie is Ronnie,” said Brad. “This is because of them.
Now the others can’t ignore this. They can’t marginalize it.”
Then he blinked. “I could fucking cry now,” he said.
He’d just been given a glimpse of the future — he felt certain
of it. Goldman Sachs was insisting that the U.S. stock market
needed to change, and that IEX was the place to change it. If
Goldman Sachs was willing to acknowledge to investors that
this new market was the best chance for fairness and stability,
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the other banks would be pressured to follow. The more orders
that flowed onto IEX, the better the experience for investors,
and the harder it would be for the banks to evade this new, fair
market. At that moment, as Goldman’s orders flowed onto IEX,
the stock market felt a bit like a river that wanted to jump its
banks. All that had been needed was for one man with a shovel
to dig a trench in an existing levee, and the pressure from the
water would finish the job — which was why men caught dig-
ging into the banks on certain stretches of the Mississippi River
were once shot on sight. Brad Katsuyama was the man with the
shovel, positioned at the river’s most vulnerable bend. Goldman
had arrived, with explosives, to help him.
Three weeks later, he stood before a group of investors who,
if they acted together, might force change upon Wall Street.
To show them that change was possible, he flashed on a big
screen the data from what had happened, for fifty-one minutes,
on December 19. The data showed, among other things, the
power of trust. Goldman had actually sent more orders to IEX
the day before, on December 18. So much more had traded on
December 19 because, on that day, for just fifty-one minutes,
Goldman had entrusted them with most of its orders for ten
seconds or more. That trust had been rewarded: The market felt
fair; 92 percent of those orders traded at the midpoint — the fan-
price — compared to 17 percent that traded at the midpoint in
Wall Street’s dark pools. (The number on the public exchanges
was even lower.) Their average trade size was twice the market
average, despite the efforts of other Wall Street banks to under-
mine them.
IEX represented a choice. IEX also made a point: that this
market which had become intentionally and overly complicated
might be understood. That, to function properly, a free finan-
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cial market didn’t need to be rigged in someone’s favor. It didn’t
need in some sick way the kickbacks, and payment for order
flow, and co-location, and all sorts of unfair advantages handed
to a small handful of traders. All it needed was for the men in
the room and other investors like them to take responsibility for
understanding it, and then to seize its controls. “The backbone
of the market is investors coming together to trade,” said Brad.
When he was finished, an investor raised his hand. “They did
it on December nineteenth,” he asked. “And then what?”
CHAPTER EIGHT
THE SPIDER AND THE FLY
T he trial of Sergey Aleynikov ran for ten days in Decem-
ber of 2010 and was notable for its paucity of informed
outsiders. High-frequency trading was a small world, and
the people who did it, or knew anything at all about it, appar-
ently had far less interest in testifying at trials than in mak-
ing their personal fortunes. The one outside expert witness on
the subject called by the government was an assistant professor
of finance at Illinois Institute of Technology named Benja-
min Van Vliet. Van Vliet had become an expert in response to
journalists’ need for one. While teaching a computer coding
course, he’d cast around for something sexy for the students
to program, and landed on high-frequency trading platforms.
In mid-2010, Forbes magazine called him out of the blue to
ask him what he thought about a fiber-optic cable that Spread
Networks had strung from Chicago to New Jersey. Van Vliet
had never heard of Spread Networks, and knew nothing about
the cable, but wound up with his name in print — which, of
course, led to more calls from journalists, who needed a high-
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frequency trading expert. Then came the flash crash, and Van
Vliet’s phone rang off the hook. Eventually, federal prosecutors
found him and asked him to serve as their expert witness in the
trial of a former Goldman Sachs high-frequency programmer.
Van Vliet still had never actually done any high-frequency
trading himself, and had little to add on the value or the gist of
what Serge Aleynikov had taken from Goldman Sachs. About
the market itself he was badly misinformed. (He described
Goldman Sachs as “the New York Yankees” of high-frequency
trading.) He turned out to have testified as an expert witness
in an earlier trial involving the theft of high-frequency trading
code, after which the judge in the case said that the idea that a
high-frequency trading program was some kind of science was
“utter baloney.”
The jury in Sergey Aleynikov’s trial consisted mainly of high
school graduates; all of the jurors lacked experience program-
ming computers. “They would bring my computer into the court-
room,” recalled Serge incredulously. “They would pull out the
hard drive and show it to the jury. As evidence!” Save for Misha
Malyshev, Serge’s onetime employer, the people who took the
stand had no credible knowledge of high-frequency trading:
how the money got made, what sort of computer code was valu-
able, and so on. Malyshev testified as a witness for the prosecution
that Goldman’s code was of no use whatsoever in the system
he’d hired Serge to build — Goldman’s code was written in a
different programming language, it was slow and clunky, it had
been designed for a firm that was trading with its own custom-
ers, and Teza, Malyshev’s firm, didn’t have customers, and so
on — but when he looked over, he saw that half the jury appeared
to be sleeping. “If I were a juror, and I wasn’t a programmer,”
said Serge, “it would be very difficult for me to understand why
I did what I did.”
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Goldman Sachs’s role in the trial was to make genuine under-
standing even more difficult. Its employees, on the witness stand,
behaved more like salesmen for the prosecution than citizens
of the state. “It’s not that they lied,” said Serge. “But they told
things that were not in their expertise.” When his former boss,
Adam Schlesinger, was asked about the code, he said that every-
thing at Goldman was proprietary. “I wouldn’t say he lied, but he
was talking about stuff that he did not understand, and so he was
misunderstood,” said Serge.
Our system of justice is a poor tool for digging out a rich
truth. What was really needed, it seemed to me, was for Serge
Aleynikov to be forced to explain what he had done, and why,
to people able to understand the explanation and judge it.
Goldman Sachs had never asked him to explain himself, and
the FBI had not sought help from anyone who actually knew
anything at all about computers or the high-frequency trad-
ing business. And so over two nights, in a private room of a
Wall Street restaurant, I convened a kind of second trial. To
serve as both jury and prosecution, I invited half a dozen people
intimately familiar with Goldman Sachs, high-frequency trad-
ing, and computer programming. All were authorities on our
abstruse new stock market; several had written high-frequency
code; one had actually developed software for Goldman’s high-
frequency traders. All were men. They’d grown up in four dif-
ferent countries between them, but all now lived in the United
States. All of them worked on Wall Street, and so, to express
themselves freely, they needed to remain anonymous. Among
them were employees of IEX.
All were naturally skeptical — of both Goldman Sachs and
Serge Aleynikov. They assumed that if Serge had been sentenced
to eight years in jail he must have done something wrong. They
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247
just hadn’t bothered to figure out what that was. All of them
had followed the case in the newspapers and noted the shiver it
had sent through the spines of Wall Street’s software developers.
Until Serge was sent to jail for doing it, it was common practice
for Wall Street programmers to take code they had worked on
when they left for new jobs. “A guy got put in jail for taking
something no one understood,” as one of Serge’s new jurors put
it. “Every tech programmer out there got the message: Take
code and you could go to jail. It was huge.” The arrest of Serge
Aleynikov had also caused a lot of people, for the first time, to
begin to use the phrase “high-frequency trading.” Another new
juror, who in 2009 had worked for a big Wall Street bank, said,
“When he was arrested, we had a meeting for all the electronic
trading personnel, to talk about a one-pager they’d drafted to be
discussed with their clients around this new topic called ‘high-
frequency trading.’ ”
The restaurant was one of those old-school Wall Street places
that charge you a thousand bucks for a private room and then
more or less challenge you to eat your way back to even. Food
and drink arrived in massive quantities: vast platters of lobster
and crab, steaks the size of desktop computer screens, smok-
ing mountains of potatoes and spinach. It was the sort of meal
cooked decades ago, for traders who spent their days trusting
their gut and their nights rewarding it; but this monstrous feast
was now being served to a collection of weedy technologists,
the people who controlled the machines that now controlled
the markets, and who had, in the bargain, put the old school
out of business. They sat around the table staring at the piles
of food, like a conquering army of eunuchs who had stumbled
into the harem of their enemy. At any rate, they made hardly a
dent. Serge, for his part, ate so little, and with such disinterest,
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that I half expected him to lift off his chair and float up to the
ceiling.
His new jurors began, interestingly, by asking him lots of per-
sonal questions. They wanted to figure out what kind of guy he
was. They took an interest, for example, in his job-market his-
tory, and noted that his behavior was pretty consistently that of
a geek who had more interest in his work than in the money the
work generated. They established fairly quickly — how, I do not
know — that he was not just smart but seriously gifted. “These
guys are usually smart in one small area,” one of them later
explained to me. “For a technologist to be so totally dominant
in so many areas is just really, really unusual.”
They then began to probe his career at Goldman Sachs. They
were surprised to learn that he had “super-user status” inside
Goldman, which is to say he was one of a handful of people
(roughly 35, in a firm that then had more than 31,000 employ-
ees) who could log onto the system as an administrator. Such
privileged access would have enabled him, at any time, to buy a
cheap USB flash drive, plug it into his terminal, and take all of
Goldman’s computer code without anyone having any idea that
he had done it. That fact alone didn’t prove anything to them. As
one pointed out to Serge directly, lots of thieves are sloppy and
careless; just because he was sloppy and careless didn’t mean he
was not a thief. On the other hand, they all agreed, there wasn’t
anything the least bit suspicious, much less nefarious, about the
manner in which he had taken what he had taken. Using a sub-
version repository to store code and deleting one’s bash history
were common practices. The latter made a great deal of sense if
you typed your passwords into command lines. In short, Serge
had not behaved like a man trying to cover his tracks. One of his
new jurors stated the obvious: “If deleting the bash history was
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249
so clever and devious, why had Goldman ever found out he’d
taken anything?”
To these new jurors, the story that the FBI found so uncon-
vincing — that Serge had taken the files because he thought
he might later like to parse the open source code contained
within — made a lot of sense. As Goldman hadn’t permitted him
to release his debugged or improved code back to the public —
even though the original free license often stated that improve-
ments must be publicly shared — the only way for him to get his
hands on these files was to take the Goldman code. That he had
also taken some code that wasn’t open source, which happened
to be in the same files as the open source code, surprised no
one. Grabbing a bunch of files that contained both open source
and non-open source code was an efficient way for him to col-
lect the open source code, even if the open source code was
the only code that interested him. It would have made far less
sense for him to hunt around the Internet for the open source
code he wanted, as it was scattered all over cyberspace. It was
also entirely plausible to them that Serge’s interest was confined
to the open source code, because that was the general-purpose
code that might be repurposed later. The Goldman proprietary
code was written specifically for Goldman’s platform; it would
have been of little use in any new system he wished to build.
(The two small pieces of code Serge had sent into Teza’s com-
puters before his arrest both came with open source licenses.)
“Even if he had taken Goldman’s whole platform, it would have
been faster and better for him to write the new platform him-
self,” said one juror.
Several times Serge surprised the jurors with his answers.
They were all shocked, for instance, that from the day Serge
first arrived at Goldman, he had been able to send Goldman’s
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source code to himself weekly, without anyone at Goldman say-
ing a word to him about it. “At Citadel, if you stick a USB drive
into your work station, someone is standing next to you within
five minutes, asking you what the hell you are doing,” said a
juror who had worked there. Most were surprised by how little
Serge had taken in relation to the whole: eight megabytes, in a
platform that consisted of nearly fifteen hundred megabytes of
code. The most cynical among them were surprised mostly by
what he had not taken.
“Did you take the strats?” asked one, referring to Goldman’s
high-frequency trading strategies.
“No,” said Serge. That was one thing the prosecutors hadn’t
accused him of.
“But that’s the secret sauce, if there is one,” said the juror. “If
you’re going to take something, take the strats.”
“I wasn’t interested in the strats,” said Serge.
“But that’s like stealing the jewelry box without the jewels,”
said another juror.
“You had super-user status!” said the first. “You could easily
have taken the strats. Why didn’t you?”
“To me, the technology really is more interesting than the
strats,” said Serge.
“You weren’t interested in how they made hundreds of mil-
lions of dollars?” asked someone else.
“Not really,” said Serge. “It’s all one big gamble, one way or
another.”
Because they had seen it before in other programmer types,
they were not totally shocked by his indifference to Goldman’s
trading, or by how far Goldman had kept him from the action.
Talking to a programmer type about the trading business was a
bit like talking to the house plumber at work in the basement
THE SPIDER AND THE FLY
251
about the card game the Mafia don was running upstairs. “He
knew so little about the business context,” one of the jurors said,
after attending both dinners. “You’d have to try to know as little
as he did.” Another said, “He knew as much as they wanted him
to know about how they made money, which was virtually noth-
ing. He wasn’t there for very long. He came in with no context.
And he spent all of his time troubleshooting.” Another said he had
found Serge to be the epitome of the programmer whose value
the big Wall Street banks tried to minimize — by using their skills
without fully admitting them into the business. “You see two
resumes from the banks,” he said. “You line them up on paper
and say maybe there’s a ten percent difference between them. But
one guy is getting paid three hundred grand and the other is get-
ting one point five million. The difference is one guy has been
given the big picture, and the other hasn’t.” Serge had never been
shown the big picture. Still, it was obvious to the jurors — even
if it wasn’t to Serge — why Goldman had hired him when it had.
With the introduction of Reg NMS in 2007, the speed of any
financial intermediary’s trading system became its most important
attribute: the speed with which it took in market data and the
speed with which it responded to that data. “Whether he knew it
or not,” said one juror, “he was hired to build Goldman’s view of
the market. No Reg NMS, no Serge in finance.”
At least some part of the reason he remained oblivious to the
nature of Goldman Sachs’s trading business, all of the jurors
noticed, was that his heart was elsewhere. “I think passion plays
a big role,” said a juror who himself had spent his entire career
writing code. “The moment he started talking about coding,
his eyes lit up.” Another added, “The fact that he kept trying to
work on open source shit even while he was at Goldman says
something about the guy.”
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They didn’t all agree that what Serge had taken had no value,
either to him or to Goldman. But what value it might have had
in creating a new system would have been trivial and indirect.
“I can guarantee you this: He did not steal code to use it on
some other system,” one said, and none of the others disagreed.
For my part, I didn’t fully understand why some parts of Gold-
man’s system might not be useful in some other system. “Gold-
man’s code base is like buying a really old house,” one of the
jurors explained. “And you take the trouble to soup it up. But
it still has the problems of a really old house. Teza was going
to build a new house, on new land. Why would you take one-
hundred-year-old copper pipes and put them in my new house?
It isn’t that they couldn’t be used; it’s that the amount of trouble
involved in making it useful is ridiculous.” A third added, “It’s
way easier to start from scratch.” Their conviction that Gold-
man’s code was not terribly useful outside of Goldman grew
even stronger when they learned — later, as Serge failed to men-
tion it at the dinners — that the new system Serge planned to
create was to be written in a different computer language than
the Goldman code.
The perplexing question, at least to me, was why Serge had
taken anything. A full month after he’d left Goldman Sachs, he
still had not touched the code he had taken. If the code was so
unimportant to him that he didn’t bother to open it up and study
it; if most of it was either so clunky or so peculiar to Goldman’s
system that it was next to useless outside Goldman — why take it?
Oddly, his jurors didn’t find this hard to understand. One put it
this way: “If Person A steals a bike from Person B, then Person
A is riding a bike to school, and Person B is walking. Person A is
better off at the expense of Person B. That is clear-cut, and most
people’s view of theft.
THE SPIDER AND THE FLY
253
“In Serge’s case, think of being at a company for three years,
and you carry a spiral notebook and write everything down.
Everything about your meetings, your ideas, products, sales, cli-
ent meetings — it’s all written down in that notebook. You leave
for your new job and take the notebook with you — as most
people do. The contents of your notebook relate to your history
at the prior company but have very little relevance to your new
job. You may never look at it again. Maybe there are some ideas,
or templates, or thoughts you can draw on. But that notebook
is related to your prior job, and you will start a new notebook
at your new job which will make the old one irrelevant. . . .
For programmers, their code is their spiral notebook. [It enables
them] to remember what they worked on — but it has very little
relevance to what they will build next. . . . He took a spiral note-
book that had very little relevance outside of Goldman Sachs.”
To the well-informed jury, the real mystery wasn’t why Serge
had done what he had done. It was why Goldman Sachs had
done what it had done. Why on earth call the FBI? Why exploit
the ignorance of both the general public and the legal system
about complex financial matters to punish this one little guy?
Why must the spider always eat the fly?
The financial insiders had many theories about this: that it
was an accident; that Goldman had called the FBI in haste and
then realized the truth, but lost control of the legal process; that
in 2009 Goldman had been on hair-trigger alert to personnel
losses in high-frequency trading, because they could see how
much money would be made from it, and thought they could
compete in the business. The jurors all had ideas about why
what had happened had happened. One of the theories was more
intriguing than the others. It had to do with the nature of a big
Wall Street bank, and the way people who worked for it, at the
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intersection of technology and trading, got ahead. As one juror
put it, “Every manager of a Wall Street tech group likes to have
people believe that his guys are geniuses. Russians, whatever.
His whole persona among his peers is that what he and his team
do can’t be replicated. When people find out that ninety-five
percent of their code is open source, it kills that perception.
What the guy can’t say, when he gets told Serge has taken some-
thing, is ‘it doesn’t matter what he took because it’s worse than
what they’ll create on their own.’ So when the security people
come to him and tell him about the downloads, he can’t say, ‘No
big deal.’ And he can’t say, ‘I don’t know what he took.’ ”
To put it another way: The process that ended with Serge
Aleynikov sitting inside two holding facilities that housed dan-
gerous offenders and then a federal prison may have started with
the concern of some Goldman Sachs manager with his bonus.
“Who is going to pull the fire alarm before they smell the fire?”
asked the juror who had advanced this last theory. “It’s always
the people who are politically motivated.” As he left dinner
with Serge Aleynikov and walked down Wall Street, he thought
about it some more. “I’m actually nauseous,” he said. “It makes
me sick.”
THE MYSTERY THE jury of Sergey Aleynikov’s peers had more trou-
ble solving was Serge himself. He appeared, and perhaps even
was, completely at peace with the world. Had you lined up the
people at those two Wall Street dinners and asked the American
public to vote for the man who had just lost his marriage, his
home, his job, his life savings, and his reputation, Serge would
have come dead last. At one point, one of the people at the table
stopped the conversation about computer code and asked, “Why
THE SPIDER AND THE FLY
255
aren’t you angry?” Serge just smiled back at him. “No, really,”
said the juror. “How do you stay so calm? I’d be fucking going
crazy.” Serge smiled again. “But what does craziness give you?”
he said. “What does negative demeanor give you as a person? It
doesn’t give you anything. You know that something happened.
Your life happened to go in that particular route. If you know
that you’re innocent, know it. But at the same time you know
you are in trouble and this is how it’s going to be.” To which he
added, “To some extent I’m glad this happened to me. I think
it strengthened my understanding of what living is all about.”
At the end of his trial, when the original jury returned with its
guilty verdict, Serge had turned to his lawyer, Kevin Marino,
and said, “You know, it did not turn out the way we had hoped.
But I have to say, it was a pretty good experience.” It was as if he
were standing outside himself and taking in the situation as an
observer. “I’ve never seen anything like it,” said Marino.
In the comfort of the Wall Street cornucopia, that notion — that
the hellish experience he’d been through had actually been good
for him — was too weird to pursue, and the jurors had quickly
returned to discussing computer code and high-frequency trad-
ing. But Serge actually believed what he had said. Before his
arrest — before he lost much of what he thought important in his
life — he went through his days and nights in a certain state of
mind: a bit self-absorbed, prone to anxiety and worry about his
status in the world. “When I was arrested, I couldn’t sleep,” he
said. “When I saw articles in the newspaper, I would tremble at
the fear of losing my reputation. Now I just smile. 1 no longer
panic. Or have panic ideas that something could go wrong.” By
the time he was first sent to jail, his wife had left him, taking
their three young daughters with her. He had no money and no
one to turn to. “He didn’t have very close friends,” his fellow
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Russian emigre Masha Leder recalled. “He never did. He’s not a
people person. He didn’t even have anyone to be power of attor-
ney.” Out of a sense of Russian solidarity, and out of pity, she
took the job — which meant, among other things, frequent trips
to visit Serge in prison. “Every time I would come to visit him
in jail, I would leave energized by him,” she said. “He radiated
so much energy and positive emotions that it was like therapy
for me to visit him. His eyes opened to how the world really is.
And he started talking to people. For the first time! He would
say: People in jail have the best stories. He could have considered
himself a tragedy. And he didn’t.”
By far the most difficult part of his experience was explain-
ing what had happened to his children. When he was arrested,
his daughters were five, three, and almost one. “I tried to put
it in the most simple terms they would understand,” said Serge.
“But the bottom line was I was apologizing for the fact that this
had happened.” In jail he was allowed three hundred minutes
a month on the phone — and for a long time the kids, when he
called them, didn’t pick up on the other end.
The holding facility in which Serge spent his first four months
was violent, and essentially nonverbal, but he didn’t find it hard
to stay out of trouble there. He even found people he could
talk to, and enjoy talking to. When they moved him to the
minimum-security prison at Fort Dix, in New Jersey, he was
still in a room crammed with hundreds of other roommates, but
he now had space to work. He remained in some physical dis-
tress, mainly because he refused to eat meat. “His body, he had
really bad times there,” said Masha Leder. “He lived on beans
and rice. He was always hungry. I’d buy him these yogurts and
he would gulp them down one after another.” His mind still
worked fine, though, and a lifetime of programming in cube
THE SPIDER AND THE FLY
257
farms had left him with the ability to focus in prison conditions.
A few months into Serge’s jail term, Masha Leder received a
thick envelope from him. It contained roughly a hundred pages
covered on both sides in Serge’s meticulous eight-point script. It
was computer code — a solution to some high-frequency trading
problem. Serge feared that if the prison guards found it, they
wouldn’t understand it, decide that it was suspicious, and con-
fiscate it.
A year after he’d been sent away, the appeal of Serge Aleynikov
was finally heard, by the Second Circuit Court of Appeals. The
judgment was swift, unlike anything his lawyer, Kevin Marino,
had seen in his career. Marino was by then working gratis for a
client who was dead broke. The very day he made his argument,
the judges ordered Serge released, on the grounds that the laws
he stood accused of breaking did not actually apply to his case.
At six in the morning on February 17, 2012, Serge received an
email from Kevin Marino saying that he was to be freed.
A few months later, Marino noticed that the government had
failed to return Serge’s passport. Marino called and asked for
it back. The passport never arrived; instead Serge, now stay-
ing with friends in New Jersey, was arrested again and taken to
jail. Once again, he had no idea what he was being arrested for,
but this time neither did the police. The New Jersey cops who
picked him up didn’t know the charges, only that he should be
held without bail, as he was deemed a flight risk. His lawyer was
just as perplexed. “When I got the call,” said Marino, “I thought
it might have something to do with Serge’s child support.” It
didn’t. A few days later, Manhattan district attorney Cyrus Vance
sent out a press release to announce that the State of New York
was charging Serge Aleynikov with “accessing and duplicating
a complex proprietary and highly confidential computer source
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code owned by Goldman Sachs.” The press release went on to
say that “ [t]his code is so highly confidential that it is known in
the industry as the firm’s ‘secret sauce,’ ” and thanked Goldman
Sachs for its cooperation. The prosecutor assigned to the case,
Joanne Li, claimed that Serge was a flight risk and needed to be
re -jailed immediately — which was strange, because Serge had
gone to and returned from Russia between the time of his first
arrest and his first jailing. (It was Li who soon fled the case— to
a job at Citigroup.)
Marino recognized the phrase “secret sauce.” It hadn’t come
from “the industry” but from his opening statement in Serge’s
first trial, when he mocked the prosecutors for treating Goldman’s
code as if it were some “secret sauce.” Otherwise Serge’s re-arrest
made no sense to him. To avoid double jeopardy, the Manhattan
DA’s office had found new crimes with which to charge Serge
for the same actions. But the sentencing guidelines for the new
crimes meant that, even if he was convicted, it was very likely
he wouldn’t have to return to jail. He’d already served time, for
crimes the court ultimately determined he had not committed.
Marino called Vance’s office. “They told me that they didn’t
need him to be punished anymore, but they need him to be held
accountable,” said Marino. “They want him to plead guilty and
let him go on time served. I told them in the politest terms pos-
sible that they can go fuck themselves. They ruined his life.”
Oddly enough, they hadn’t. “Inside of me I was completely
witnessing,” said Serge, about the night of his re-arrest. “There
was no fear, no panic, no negativity.” His children had reat-
tached themselves to him, and he had a new world of people to
whom he felt close. He thought he was living his life as well as it
had ever been lived. He’d even started a memoir, to explain what
had happened to anyone who might be interested. He began:
THE SPIDER AND THE FLY
259
If the incarceration experience doesn’t break your spirit, it
changes you in a way that you lose many fears. You begin to
realize that your life is not ruled by your ego and ambition and
that it can end any day at any time. So why worry? You learn
that just like on the street, there is life in prison, and random
people get there based on the jeopardy of the system. The pris-
ons are filled by people who crossed the law, as well as by those
who were incidentally and circumstantially picked and crushed
by somebody else’s agenda. On the other hand, as a vivid ben-
efit, you become very much independent of material property
and learn to appreciate very simple pleasures in life such as the
sunlight and morning breeze.
EPILOGUE
RIDING THE
WALL STREET TRAIL
F or at least a few members of the Women’s Adventure Club
of Centre County, Pennsylvania, the weather was never
much of an issue. The Women’s Adventure Club had been
created by Lisa Wandel, an administrator at Penn State Uni-
versity, after she realized that many women were afraid to hike
alone in the woods. The club now had more than seven hundred
members, and its sense of adventure had expanded far beyond
a walk in the woods. Between them the four women who met
me on their bicycles beside the Pennsylvania road had: learned
the flying trapeze, swum the Chesapeake Bay, and won silver at
the downhill mountain biking world championships; they had
finished a road bike race called the Gran Fondo “Masochistic
Metric,” a footrace called the Tough Mudder, and three separate
twenty-four-hour-long mountain bike races; they had gradu-
ated from race car driving school and made thirteen Polar Bear
Plunges in some local river in the dead of winter. After studying
the Women’s Adventure Club’s website, Ronan had said, “It’s a
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bunch of lunatic women who meet up and do dangerous shit; I
got to get my wife into it.”
In the bleak January light we pedaled onto Route 45 out of
Boalsburg, Pennsylvania, heading east, along what was once the
route for the stagecoach that ran from Philadelphia to Erie. It
was nine in the morning, and still below freezing, with a stiff
breeze lowering the windchill to eleven degrees. The views
were of farms and fallow brown fields, and the road was empty
except for the occasional pickup truck, roaring past us with real
anger. “They hate bikers,” explained one of the women adven-
turers mildly. “They try to see how close they can get.”
The women rode this stretch of road every so often, and had
noticed when the fiber-optic line was being laid beside it, back
in 2010. From time to time one of the road’s two lanes was
closed by the line’s construction crews. You’d see these motley
queues of bikes, cars, pickup trucks, Amish horse-drawn carts,
and farm equipment waiting for the tail end of the oncoming
traffic. The crews trenched the ground between the paved road
and the farms, making it difficult for the Amish in their wagons
to get back to their homes — sometimes you’d see these Amish
kids, the girls in their pretty purple dresses, hopping off the
wagon and leaping over the trench. The members of the Wom-
en’s Adventure Club had been told by a local government official
that the fiber-optic line was a government project to provide
high-speed Internet access to local colleges. Hearing that it was
actually a private project to provide a 3-millisecond edge to
high-frequency traders, they had some new questions about it.
“How does a private line get access to a public right-of-way?”
asked one. “I’m really curious to know that.”
RIDING THE WALL STREET TRAIL
263
WE’RE IN A transition here. That’s what the Goldman Sachs peo-
ple said when you asked them, in so many words, how they
could have gone from bringing the wrath of U.S. prosecutors
down upon Serge Aleynikov for emailing their high-frequency
trading computer code to himself, to helping Brad Katsuyama
change the U.S. stock market in ways that would render Gold-
man’s high-frequency trading computer code worthless.
There was a connection between Serge Aleynikov and
Goldman’s behavior on December 19, 2013. The trial and the
publicity that attended it caused a lot of people to think more
rigorously about the value of Goldman Sachs’s high-frequency
trading code. High-frequency trading had a winner-take-all
aspect: The fastest predator took home the fattest prey. By 2013
the people charged with determining Goldman’s stock market
strategy had concluded that Goldman wasn’t very good at this
new game, and that Goldman was unlikely ever to be very good
at it. The high-frequency traders would always be faster than
Goldman Sachs — or any other big Wall Street bank. The people
who ran Goldman Sachs’s stock market department had come to
understand that what Serge had taken wasn’t worth stealing — at
least not by anyone whose chief need was speed.
The trouble for any big Wall Street bank wasn’t simply that a
big bureaucracy was ill-suited to keeping pace with rapid tech-
nological change, but that the usual competitive advantages of a
big Wall Street bank were of little use in high-frequency trad-
ing. A big Wall Street bank’s biggest advantage was its access to
vast amounts of cheap risk capital and, with that, its ability to
survive the ups and downs of a risky business. That meant little
when the business wasn’t risky and didn’t require much capital.
High-frequency traders went home every night with no posi-
tion in the stock market. They traded in the market the way card
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counters in a casino played blackjack: They played only when
they had an edge. That’s why they were able to trade for five
years without losing money on a single day.
A big Wall Street bank really had only one advantage in an
ever-faster financial market: first shot at its own customers’ stock
market trades. So long as the customers remained inside the dark
pool, and in the dark, the bank might profit at their expense.
But even here the bank would never do the job as efficiently
or thoroughly as a really good HFT. It was hard to resist the
pressure to hand the prey over to the more skilled predator, to
ensure that the kill was done quickly and discreetly, and then,
after the kill, to join in the feast as a kind of junior partner —
though more junior than partner. In the dark pool arbitrage IEX
had witnessed, for instance, HFT captured about 85 percent of
the gains, leaving the bank with just 15 percent.
The new structure of the U.S. stock market had removed the big
Wall Street banks from their historic, lucrative role as intermediary.
At the same time it created, for any big bank, some unpleasant risks:
that the customer would somehow figure out what was happening
to his stock market orders. And that the technology might some-
how go wrong. If the markets collapsed, or if another flash crash
occurred, the high-frequency traders would not take 85 percent of
the blame, or bear 85 percent of the costs of the inevitable lawsuits.
The banks would bear the lion’s share of the blame and the costs.
The relationship of the big Wall Street banks to the high-frequency
traders, when you thought about it, was a bit like the relationship
of the entire society to the big Wall Street banks. When things
went well, the HFT guys took most of the gains; when things went
badly, the HFT guys vanished and the banks took the losses.
Goldman had figured all of this out — probably before the
other big Wall Street banks, to judge from its treatment of IEX.
RIDING THE WALL STREET TRAIL
265
By December 19, 2013, the people newly installed on top of
Goldman Sachs’s stock market operations, Ron Morgan and
Brian Levine, wanted to change the way the market worked.
They were obviously sincere. They truly believed that the mar-
ket at the heart of the world’s largest economy had grown too
complex, and was likely to experience some catastrophic failure.
But they also were trying to put an end to a game they could
never win — or control. And so they’d flipped a switch, and sent
lots of their customers’ stock market orders to IEX. When they
did this they started a process that, if allowed to play out, would
take billions from Wall Street and return it to investors. It would
also create fairness.
A big Wall Street bank was a complex environment. There
were people inside Goldman Sachs less than pleased by what
Levine and Morgan had done. And after December 19 the firm
had retreated, just a little bit. It was hard even for Brad Kat-
suyama to know why. Was it changing its collective mind? Had
it underestimated the cost of being the first mover? Was it too
much to ask Goldman Sachs to look up from short-term profit
and study the landscape down the road? It was possible that even
Goldman Sachs did not know the answers to those questions.
Whatever the answers, something Brian Levine had said still
made a lot of sense. “There will be a lot of resistance,” he’d said.
“There will be a lot of resistance. Because a tremendous infra-
structure has been built up around this.”
It’s worth performing a Goldman Sachs-like cost-benefit anal-
ysis of this infrastructure, from the point of view of the economy
it is meant to serve. The benefit: Stock market prices adjust to
new information a few milliseconds faster than they otherwise
might. The costs make for a longer list. One obvious cost is the
instability introduced into the system when its primary goal is
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no longer stability but speed. Another is the incalculable billions
collected by financial intermediaries. That money is a tax on
investment, paid for by the economy; and the more that produc-
tive enterprise must pay for capital, the less productive enterprise
there will be. Another cost, harder to measure, was the influence
all this money exerted, not just on the political process but on
people’s decisions about what to do with their lives. The more
money to be made gaming the financial markets, the more peo-
ple would decide they were put on earth to game the financial
markets — and create romantic narratives to explain to themselves
why a life spent gaming the financial markets is a purposeful life.
And then there is maybe the greatest cost of all: Once very smart
people are paid huge sums of money to exploit the flaws in the
financial system, they have the spectacularly destructive incen-
tive to screw the system up further, or to remain silent as they
watch it being screwed up by others.
The cost, in the end, is a tangled-up financial system. Untan-
gling it requires acts of commercial heroism — and even then
the fix might not work. There was simply too much more easy
money to be made by elites if the system worked badly than if
it worked well. The whole culture had to want to change. “We
know how to cure this,” as Brad had put it. “It’s just a matter of
whether the patient wants to be treated.”
FOR A LONG stretch along the Spread Networks line, there was no
happy place for a rider to stop. The road’s shoulder was narrow,
and the cornfields beside it were planted with No Trespassing
signs. Apart from the plastic soda bottle and the carcasses of deer
killed by the speeding pickup trucks, and a shop or two, the
landscape looked a lot like it once did from the Philadelphia-
RIDING THE WALL STREET TRAIL
267
Erie stagecoach. The most insistent signs of modernity were the
white poles with their bright orange domes, every few hundred
yards, installed three and a half years earlier. After ten miles
or so we found an open field without a sign and pulled over
beside a white-and-orange pole. The poles stretched into the
distance in both directions. An ambitious hiker or cyclist could
follow them all the way to a building beside the Nasdaq stock
exchange, in New Jersey; or, if he turned and headed west, to
the Chicago Mercantile Exchange.
Across the road was a local landmark: the Red Round Barn.
One of the women repeated a rural legend, saying that the red
barn had been built in the round so that mice had no corners in
which to hide. “People don’t know how to live in a world that
is transparent,” Brad Katsuyama had said, and mice were prob-
ably no better at it. Beyond the barn was a mountain. On top
of the mountain was a microwave tower — a string of them, in
fact, perched on the mountains above the valley in which the
line was buried.
It takes roughly 8 milliseconds to send a signal from Chi-
cago to New York and back by microwave signal, or about 4.5
milliseconds less than to send it inside an optical fiber. When
Spread Networks was laying its line, the conventional wisdom
was that microwave could never replace fiber. It might be faster,
but whatever was going on between New York and Chicago
required huge amounts of complicated data to be sent back and
forth, and a microwave signal couldn’t transmit nearly as much
data as a signal in a fiber-optic cable. Microwave signals needed
a direct line of sight to get to wherever they were going, with
nothing in between. And microwave signals didn’t travel well in
bad weather.
But what if microwave technology improved? And what if the
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data essential for some high-frequency trader to gain an edge
over investors in the market wasn’t actually all that complicated?
And what if the tops of mountains afforded a direct line of sight
between distant financial markets?
The risks taken by high-frequency traders were not the
usual risks taken by people who purport to sit in the middle of
markets, buying from sellers and selling to buyers. They didn’t
risk buying a bunch of shares in a falling stock, or selling a
bunch of shares in a rising one. They were too skittish and well
informed for that — with one obvious exception. They were all
exposed to the risk that the entire stock market would move,
by a lot. A big high-frequency trader might “make markets”
in several thousand individual stocks in New Jersey. As the
purpose of these buy and sell orders was not to buy and sell
stock but to tease out market information from others, the
orders would typically be tiny in each stock: 100 shares bid,
100 shares offered. There was little risk in any individual case
but great risk in the aggregate. If, say, some piece of bad news
hit the market, and the entire stock market fell, it would take
all the individual stocks with it. Any high-frequency traders
who did not receive advance warning would be left owning
100 shares each of several thousand different stocks they did
not want to own, with big losses in each.
But the U.S. stock market had an accidental beauty to it, from
the point of view of a trader who wished to trade only when he
had some edge. The big moves occurred first in the futures mar-
ket in Chicago, before sweeping into the markets for individual
stocks. If you were able to detect these moves, and warn your
computers in New Jersey of price movements in Chicago, you
could simply withdraw your bids for individual stocks before
the market fully realized that it had fallen. That’s why it was so
RIDING THE WALL STREET TRAIL
269
important for high-frequency traders to move information faster
than everyone else from the futures exchange in Chicago to the
stock markets in New Jersey: to flee the market before others.
This race was run not just against ordinary investors, or even
Wall Street banks, but also against other high-frequency traders.
The first high-frequency trader to reach New Jersey with the
news could sell 100 shares each in thousands of different stocks
to the others.
After some obligatory staring at the Red Round Barn, we
jumped back on our bikes and continued. A few miles down
the road, we turned onto the road leading to the summit of a
mountain with a tower on top of it. The woman who had won
the silver medal at the downhill mountain biking world cham-
pionships sighed. “I like going down more than going up,” she
said, then took off at speed, leaving everyone else behind. Soon
I was watching the backs of female riders, climbing rapidly. It
could have been worse: The Appalachians are mercifully old
and worn. This particular mountain, once the size of a Swiss
Alp, had been shrunken by half a billion years of bad weather.
It was now almost beneath the dignity of the Women’s Adven-
ture Club.
It took maybe twenty minutes to puff to the top of the road,
where the women adventurers stood waiting. From there we
turned onto a smaller road leading into the woods, headed in the
direction of the mountaintop. We rode through the woods for
a few hundred yards until the road ended — or, rather, was bar-
ricaded by a new metal gate. There we ditched our bikes, leapt
over the signs warning of various dangers, and hiked onto a gravel
path that continued to the mountaintop. The women didn’t think
twice about any of this: To them it was just another adventure. A
few minutes later the microwave tower came into view.
270
FLASH BOYS
“I climbed up one of these towers once,” one of the women
said a bit wistfully.
The tower was 180 feet high, with no ladder, and festooned
with electrical equipment. “Why did you do that?” I asked.
“I was pregnant and it was a lot of work,” she replied, as if that
answered the question.
“And that’s why your baby had seven toes!” hooted one of the
other women, and they all laughed.
If one of the women had hopped over the fence around the
tower and climbed to the top, she would have had an unob-
structed view of the next tower and, from there, the tower
beyond. This was just one in a chain of thirty-eight towers that
carried news of the direction of the stock market from Chicago
to New Jersey: up or down; buy or sell; in or out. We walked
around the site. The tower showed some signs of age. It could
have been erected some time ago, for some other purpose. But
the ancillary equipment— the generator, a concrete bunker to
hold God knows what — was all shiny and new. The repeaters
that amplify financial signals resembled kettle drums, bolted
onto the side of the tower: These were also new. The speed
with which they transmitted signals, and with which the com-
puters on either end of the chain of towers turned the signals
into financial actions, were still as difficult to comprehend as the
forces of nature once had been. Anything said about them could
be believed. People no longer are responsible for what happens in the
market, because computers make all the decisions. And in the begin-
ning God created the heaven and the earth.
I noticed, before we left, a metal plate attached to the fence
around the tower. On it was a Federal Communications Com-
mission license number: 1215095. The number, along with an
Internet connection, was enough to lead an inquisitive person to
RIDING THE WALL STREET TRAIL
271
the story behind the tower. The application to use the tower to
send a microwave signal had been filed in July 2012, and it had
been filed by . . . well, it isn’t possible to keep any of this secret
anymore. A day’s journey in cyberspace would lead anyone who
wished to know it into another incredible but true Wall Street
story, of hypocrisy and secrecy and the endless quest by human
beings to gain a certain edge in an uncertain world. All that one
needed to discover the truth about the tower was the desire to
know it.
ACKNOWLEDGMENTS
T he U.S. financial system has experienced many changes
since I first entered it, and one of them is in its relationship
to any writer who attempts to figure out what’s going on
inside of it. Wall Street firms — not just the big banks but all of
them — have grown greatly more concerned than they were in
the late 1980s with what some journalist might say about them.
To judge only from their behavior, they have a lot more to fear.
They are more likely than they once were to seek to shape any
story told about them. At the same time, the people who work
in these firms have grown more cynical about them, and more
willing to reveal their inner workings, so long as their name
is not attached to these revelations. As a result, I am unable to
thank many of the people inside banks and high-frequency trad-
ing firms and stock exchanges who spoke openly about them,
and helped me to comprehend the seemingly incomprehensible.
Some other people not mentioned in this book were impor-
274
ACKNOWLEDGMENTS
tant to its creation. Jacob Weisberg read an early draft and had
shrewd things to say about it. At different times and in different
ways, Dacher Keltner, Tabitha Soren, and Doug Stumpf listened
to me drone on at length about what I was working on, and
responded with thoughts that never would have occurred to me.
Jaime Lalinde helped me, invaluably, in researching the case of
Serge Aleynikov. I apologize to Ryan Harrington, at W. W.
Norton, for sending him chasing around for illustrations that
I thought might be useful but which turned out to be a dumb
idea. He did it very well, though.
Starling Lawrence has edited my books since I first started
writing them, with his peculiar combination of encouragement
and detachment. He edited this one, too, and I’ve never ben-
efited so much from his unwillingness to allow me to enjoy
even the briefest moment of self-satisfaction. The third member
of our team, Janet Byrne, is the finest copy editor I have ever
worked with. Many mornings her enthusiasm got me out of my
bed, and many evenings her diligence prevented me from get-
ting back into it.
Finally, I’d like not only to thank the employees of IEX but
also to list them by name, so one day people can look back
and know them. They are: Lana Amer, Benjamin Aisen, Daniel
Aisen, Joshua Blackburn, Donald Bohemian, James Cape, Fran-
cis Chung, Adrian Facini, Stan Feldman, Brian Foley, Ramon
Gonzalez, Bradley Katsuyama, Craig Katsuyama, Joe Kondel,
Gerald Lam, Frank Lennox, Tara McKee, Rick Molakala, Tom
O’Brien, Robert Park, Stefan Parker, Zoran Perkov, Eric Quin-
lan, Ronan Ryan, Rob Salman, Prerak Sanghvi, Eric Schmid,
John Schwall, Constantine Sokoloff, Beau Tateyama, Matt
Trudeau, Larry Yu, Allen Zhang, and Billy Zhao.
(continued from front flap)
good for your blood pressure, because if
you have any contact with the market, even
a retirement account, this story is happening
to you. But in the end, Flash Boys is an
uplifting read. Here are people who have
somehow preserved a moral sense in an envi-
ronment where you don’t get paid for that;
they have perceived an institutionalized
injustice and are willing to go to war to fix it.
MICHAEL LEWIS is the best-selling
author of Liar’s Poker, Moneyball , The Blind
Side, and The Big Short. He lives in Berkeley,
California, with his wife and three children.
JACKET DESIGN BY PETE GARCEAU
PRINTED IN THE UNITED STATES OF AMERICA
W. W. NORTON & COMPANY
NEW YORK • LONDON
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praise for MICHAEL LE W I S
“I read Michael Lewis for the same reason I watch Tiger Woods. I'll never play like
that. But it’s good to be reminded every now and again what genius looks like.”
— MALCOLM GLADWELL, New York Times Book Review
fro,n FLASH BOYS
“By the summer of 2013, the world’s financial markets were designed to maximize
the number of collisions between ordinary investors and high-frequency traders
at the expense of ordinary investors and for the benefit of high-frequency traders,
exchanges, Wall Street banks, and online brokerage firms. Around those collisions
an entire ecosystem had arisen.”